Search (31 results, page 1 of 2)

0.013415024 = product of:
  0.04024507 = sum of:
    0.008347853 = weight(_text_:in in 1443) [ClassicSimilarity], result of:
      0.008347853 = score(doc=1443,freq=28.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.14058185 = fieldWeight in 1443, product of:
          5.2915025 = tf(freq=28.0), with freq of:
            28.0 = termFreq=28.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1443)
    0.031897217 = weight(_text_:und in 1443) [ClassicSimilarity], result of:
      0.031897217 = score(doc=1443,freq=58.0), product of:
        0.09675359 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.043654136 = queryNorm
        0.32967478 = fieldWeight in 1443, product of:
          7.615773 = tf(freq=58.0), with freq of:
            58.0 = termFreq=58.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1443)
  0.33333334 = coord(2/6)

Footnote

Rez. in: Information - Wissenschaft und Praxis 56(2004) H.1, S.61-62 (D. Lewandowski): "Die Autoren des vorliegenden Bandes haben sich in den letzten Jahren durch ihre zahlreichen Veröffentlichungen zum Verhalten von Suchmaschinen-Nutzern einen guten Namen gemacht. Das nun erschienene Buch bietet eine Zusammenfassung der verstreut publizierten Aufsätze und stellt deren Ergebnisse in den Kontext eines umfassenderen Forschungsansatzes. Spink und Jansen verwenden zur Analyse des Nutzungsverhaltens query logs von Suchmaschinen. In diesen werden vom Server Informationen protokolliert, die die Anfragen an diesen Server betreffen. Daten, die aus diesen Dateien gewonnen werden können, sind unter anderem die gestellten Suchanfragen, die Adresse des Rechners, von dem aus die Anfrage gestellt wurde, sowie die aus den Trefferlisten ausgewählten Dokumente. Der klare Vorteil der Analyse von Logfiles liegt in der Möglichkeit, große Datenmengen ohne hohen personellen Aufwand erheben zu können. Die Daten einer Vielzahl anonymer Nutzer können analysiert werden; ohne dass dabei die Datenerhebung das Nutzerverhalten beeinflusst. Dies ist bei Suchmaschinen von besonderer Bedeutung, weil sie im Gegensatz zu den meisten anderen professionellen Information-Retrieval-Systemen nicht nur im beruflichen Kontext, sondern auch (und vor allem) privat genutzt werden. Das Bild des Nutzungsverhaltens wird in Umfragen und Laboruntersuchungen verfälscht, weil Nutzer ihr Anfrageverhalten falsch einschätzen oder aber die Themen ihrer Anfragen nicht nennen möchten. Hier ist vor allem an Suchanfragen, die auf medizinische oder pornographische Inhalte gerichtet sind, zu denken. Die Analyse von Logfiles ist allerdings auch mit Problemen behaftet: So sind nicht alle gewünschten Daten überhaupt in den Logfiles enthalten (es fehlen alle Informationen über den einzelnen Nutzer), es werden keine qualitativen Informationen wie etwa der Grund einer Suche erfasst und die Logfiles sind aufgrund technischer Gegebenheiten teils unvollständig. Die Autoren schließen aus den genannten Vor- und Nachteilen, dass sich Logfiles gut für die Auswertung des Nutzerverhaltens eignen, bei der Auswertung jedoch die Ergebnisse von Untersuchungen, welche andere Methoden verwenden, berücksichtigt werden sollten.
Den Autoren wurden von den kommerziellen Suchmaschinen AltaVista, Excite und All the Web größere Datenbestände zur Verfügung gestellt. Die ausgewerteten Files umfassten jeweils alle an die jeweilige Suchmaschine an einem bestimmten Tag gestellten Anfragen. Die Daten wurden zwischen 199'] und 2002 erhoben; allerdings liegen nicht von allen Jahren Daten von allen Suchmaschinen vor, so dass einige der festgestellten Unterschiede im Nutzerverhalten sich wohl auf die unterschiedlichen Nutzergruppen der einzelnen Suchmaschinen zurückführen lassen. In einem Fall werden die Nutzergruppen sogar explizit nach den Suchmaschinen getrennt, so dass das Nutzerverhalten der europäischen Nutzer der Suchmaschine All the Web mit dem Verhalten der US-amerikanischen Nutzer verglichen wird. Die Analyse der Logfiles erfolgt auf unterschiedlichen Ebenen: Es werden sowohl die eingegebenen Suchbegriffe, die kompletten Suchanfragen, die Such-Sessions und die Anzahl der angesehenen Ergebnisseiten ermittelt. Bei den Suchbegriffen ist besonders interessant, dass die Spannbreite der Informationsbedürfnisse im Lauf der Jahre deutlich zugenommen hat. Zwar werden 20 Prozent aller eingegebenen Suchbegriffe regelmäßig verwendet, zehn Prozent kamen hingegen nur ein einziges Mal vor. Die thematischen Interessen der Suchmaschinen-Nutzer haben sich im Lauf der letzten Jahre ebenfalls gewandelt. Während in den Anfangsjahren viele Anfragen aus den beiden Themenfeldern Sex und Technologie stammten, gehen diese mittlerweile zurück. Dafür nehmen Anfragen im Bereich E-Commerce zu. Weiterhin zugenommen haben nicht-englischsprachige Begriffe sowie Zahlen und Akronyme. Die Popularität von Suchbegriffen ist auch saisonabhängig und wird durch aktuelle Nachrichten beeinflusst. Auf der Ebene der Suchanfragen zeigt sich weiterhin die vielfach belegte Tatsache, dass Suchanfragen in Web-Suchmaschinen extrem kurz sind. Die durchschnittliche Suchanfrage enthält je nach Suchmaschine zwischen 2,3 und 2,9 Terme. Dies deckt sich mit anderen Untersuchungen zu diesem Thema. Die Länge der Suchanfragen ist in den letzten Jahren leicht steigend; größere Sprünge hin zu längeren Anfragen sind jedoch nicht zu erwarten. Ebenso verhält es sich mit dem Einsatz von Operatoren: Nur etwa in jeder zehnten Anfrage kommen diese vor, wobei die Phrasensuche am häufigsten verwendet wird. Dass die SuchmaschinenNutzer noch weitgehend als Anfänger angesehen werden müssen, zeigt sich auch daran, dass sie pro Suchanfrage nur drei oder vier Dokumente aus der Trefferliste tatsächlich sichten.
In Hinblick auf die Informationsbedürfnisse ergibt sich eine weitere Besonderheit dadurch, dass Suchmaschinen nicht nur für eine Anfrageform genutzt werden. Eine "Spezialität" der Suchmaschinen ist die Beantwortung von navigationsorientierten Anfragen, beispielsweise nach der Homepage eines Unternehmens. Hier wird keine Menge von Dokumenten oder Fakteninformation verlangt; vielmehr ist eine Navigationshilfe gefragt. Solche Anfragen nehmen weiter zu. Die Untersuchung der Such-Sessions bringt Ergebnisse über die Formulierung und Bearbeitung der Suchanfragen zu einem Informationsbedürfnis zutage. Die Sessions dauern weit überwiegend weniger als 15 Minuten (dies inklusive Sichtung der Dokumente!), wobei etwa fünf Dokumente angesehen werden. Die Anzahl der angesehenen Ergebnisseiten hat im Lauf der Zeit abgenommen; dies könnte darauf zurückzuführen sein, dass es den Suchmaschinen im Lauf der Zeit gelungen ist, die Suchanfragen besser zu beantworten, so dass sich brauchbare Ergebnisse öfter bereits auf der ersten Ergebnisseite finden. Insgesamt bestätigt sich auch hier das Bild vom wenig fortgeschrittenen Suchmaschinen-Nutzer, der nach Eingabe einer unspezifischen Suchanfrage schnelle und gute Ergebnisse erwartet. Der zweite Teil des Buchs widmet sich einigen der bei den Suchmaschinen-Nutzern populären Themen und analysiert das Nutzerverhalten bei solchen Suchen. Dabei werden die eingegebenen Suchbegriffe und Anfragen untersucht. Die Bereiche sind E-Commerce, medizinische Themen, Sex und Multimedia. Anfragen aus dem Bereich E-Commerce sind in der Regel länger als allgemeine Anfragen. Sie werden seltener modifiziert und pro Anfrage werden weniger Dokumente angesehen. Einige generische Ausdrücke wie "shopping" werden sehr häufig verwendet. Der Anteil der E-Commerce-Anfragen ist hoch und die Autoren sehen die Notwendigkeit, spezielle Suchfunktionen für die Suche nach Unternehmenshomepages und Produkten zu erstellen bzw. zu verbessern. Nur zwischen drei und neun Prozent der Anfragen beziehen sich auf medizinische Themen, der Anteil dieser Anfragen nimmt tendenziell ab. Auch der Anteil der Anfragen nach sexuellen Inhalten dürfte mit einem Wert zwischen drei und knapp 1'7 Prozent geringer ausfallen als allgemein angenommen.
Der relativ hohe Wert von 17 Prozent stammt allerdings aus dem Jahr 1997; seitdem ist eine deutliche Abnahme zu verzeichnen. Betont werden muss außerdem, dass Anfragen nach sexuellen Inhalten nicht mit denen nach Pornographie gleichzusetzen sind. Die Suche nach Multimedia-Inhalten hat sich von den allgemeinen Suchinterfaces der Suchmaschinen hin zu speziellen Suchmasken verschoben, die inzwischen von allen großen Suchmaschinen angeboten werden. Die wichtigste Aussage aus den untersuchten Daten lautet, dass die Suche nach Multimedia-Inhalten komplexer und vor allem interaktiver ist als die übliche Websuche. Die Anfragen sind länger und enthalten zu einem deutlich größeren Teil Operatoren. Bei der Bildersuche stellen weiterhin sexuell orientierte Anfragen den höchsten Anteil. Bei der Bilderund Video-Suche sind die Anfragen deutlich länger als bei der regulären Suche; bei der Audio-Suche sind sie dagegen kürzer. Das vorliegende Werk bietet die bisher umfassendste Analyse des Nutzerverhaltens bezüglich der Web-Suche; insbesondere wurden bisher keine umfassenden, auf längere Zeiträume angelegten Studien vorgelegt, deren Ergebnisse wie im vorliegenden Fall direkt vergleichbar sind. Die Ergebnisse sind valide und ermöglichen es Suchmaschinen-Anbietern wie auch Forschern, künftige Entwicklungen stärker als bisher am tatsächlichen Verhalten der Nutzer auszurichten. Das Buch beschränkt sich allerdings auf die US-amerikanischen Suchmaschinen und deren Nutzer und bezieht nur bei All the Web die europäischen Nutzer ein. Insbesondere die Frage, ob die europäischen oder auch deutschsprachigen Nutzer anders suchen als die amerikanischen, bleibt unbeantwortet. Hier wären weitere Forschungen zu leisten."

0.008438686 = product of:
  0.025316058 = sum of:
    0.0075724614 = weight(_text_:in in 2742) [ClassicSimilarity], result of:
      0.0075724614 = score(doc=2742,freq=4.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.12752387 = fieldWeight in 2742, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=2742)
    0.017743597 = product of:
      0.035487194 = sum of:
        0.035487194 = weight(_text_:22 in 2742) [ClassicSimilarity], result of:
          0.035487194 = score(doc=2742,freq=2.0), product of:
            0.15286934 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043654136 = queryNorm
            0.23214069 = fieldWeight in 2742, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=2742)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)

Abstract

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.

Date

22. 3.2009 17:49:11

0.002145118 = product of:
  0.0128707085 = sum of:
    0.0128707085 = weight(_text_:in in 6980) [ClassicSimilarity], result of:
      0.0128707085 = score(doc=6980,freq=26.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.2167489 = fieldWeight in 6980, product of:
          5.0990195 = tf(freq=26.0), with freq of:
            26.0 = termFreq=26.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.03125 = fieldNorm(doc=6980)
  0.16666667 = coord(1/6)

Abstract

In previous articles, we reported the state of Web searching in 1997 (Jansen, Spink, & Saracevic, 2000) and in 1999 (Spink, Wolfram, Jansen, & Saracevic, 2001). Such snapshot studies and statistics on Web use appear regularly (OCLC, 1999), but provide little information about Web searching trends. In this article, we compare and contrast results from our two previous studies of Excite queries' data sets, each containing over 1 million queries submitted by over 200,000 Excite users collected on 16 September 1997 and 20 December 1999. We examine how public Web searching changing during that 2-year time period. As Table 1 shows, the overall structure of Web queries in some areas did not change, while in others we see change from 1997 to 1999. Our comparison shows how Web searching changed incrementally and also dramatically. We see some moves toward greater simplicity, including shorter queries (i.e., fewer terms) and shorter sessions (i.e., fewer queries per user), with little modification (addition or deletion) of terms in subsequent queries. The trend toward shorter queries suggests that Web information content should target specific terms in order to reach Web users. Another trend was to view fewer pages of results per query. Most Excite users examined only one page of results per query, since an Excite results page contains ten ranked Web sites. Were users satisfied with the results and did not need to view more pages? It appears that the public continues to have a low tolerance of wading through retrieved sites. This decline in interactivity levels is a disturbing finding for the future of Web searching. Queries that included Boolean operators were in the minority, but the percentage increased between the two time periods. Most Boolean use involved the AND operator with many mistakes. The use of relevance feedback almost doubled from 1997 to 1999, but overall use was still small. An unusually large number of terms were used with low frequency, such as personal names, spelling errors, non-English words, and Web-specific terms, such as URLs. Web query vocabulary contains more words than found in large English texts in general. The public language of Web queries has its own and unique characteristics. How did Web searching topics change from 1997 to 1999? We classified a random sample of 2,414 queries from 1997 and 2,539 queries from 1999 into 11 categories (Table 2). From 1997 to 1999, Web searching shifted from entertainment, recreation and sex, and pornography, preferences to e-commerce-related topics under commerce, travel, employment, and economy. This shift coincided with changes in information distribution on the publicly indexed Web.

0.0019955188 = product of:
  0.011973113 = sum of:
    0.011973113 = weight(_text_:in in 3454) [ClassicSimilarity], result of:
      0.011973113 = score(doc=3454,freq=10.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.20163295 = fieldWeight in 3454, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=3454)
  0.16666667 = coord(1/6)

Abstract

Major Web search engines, such as AItaVista, are essential tools in the quest to locate online information. This article reports research that used transaction log analysis to examine the characteristics and changes in AItaVista Web searching that occurred from 1998 to 2002. The research questions we examined are (1) What are the changes in AItaVista Web searching from 1998 to 2002? (2) What are the current characteristics of AItaVista searching, including the duration and frequency of search sessions? (3) What changes in the information needs of AItaVista users occurred between 1998 and 2002? The results of our research show (1) a move toward more interactivity with increases in session and query length, (2) with 70% of session durations at 5 minutes or less, the frequency of interaction is increasing, but it is happening very quickly, and (3) a broadening range of Web searchers' information needs, with the most frequent terms accounting for less than 1% of total term usage. We discuss the implications of these findings for the development of Web search engines.

0.001821651 = product of:
  0.010929906 = sum of:
    0.010929906 = weight(_text_:in in 1730) [ClassicSimilarity], result of:
      0.010929906 = score(doc=1730,freq=12.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.18406484 = fieldWeight in 1730, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1730)
  0.16666667 = coord(1/6)

Abstract

Purpose - The purpose of this paper is to examine the way in which end user searching on the web has become the primary method of locating digital images for many people. This paper seeks to investigate how users structure these image queries. Design/methodology/approach - This study investigates the structure and formation of image queries on the web by mapping a sample of web queries to three known query classification schemes for image searching (i.e. Enser and McGregor, Jörgensen, and Chen). Findings - The results indicate that the features and attributes of web image queries differ relative to image queries utilized on other information retrieval systems and by other user populations. This research points to the need for five additional attributes (i.e. collections, pornography, presentation, URL, and cost) in order to classify web image queries, which were not present in any of the three prior classification schemes. Research limitations/implications - Patterns in web searching for image content do emerge that inform the design of web-based multimedia systems, namely, that there is a high interest in locating image collections by web searchers. Objects and people images are the predominant interest for web searchers. Cost is a factor for web searching. This knowledge of the structure of web image queries has implications for the design of image information retrieval systems and repositories, especially in the area of automatic tagging of images with metadata. Originality/value - This is the first research that examines whether or not one can apply image query classifications schemes to web image queries.

0.001821651 = product of:
  0.010929906 = sum of:
    0.010929906 = weight(_text_:in in 2948) [ClassicSimilarity], result of:
      0.010929906 = score(doc=2948,freq=12.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.18406484 = fieldWeight in 2948, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2948)
  0.16666667 = coord(1/6)

Abstract

In this research we investigate the effect of search engine brand on the evaluation of searching performance. Our research is motivated by the large amount of search traffic directed to a handful of Web search engines, even though many have similar interfaces and performance. We conducted a laboratory experiment with 32 participants using a 42 factorial design confounded in four blocks to measure the effect of four search engine brands (Google, MSN, Yahoo!, and a locally developed search engine) while controlling for the quality and presentation of search engine results. We found brand indeed played a role in the searching process. Brand effect varied in different domains. Users seemed to place a high degree of trust in major search engine brands; however, they were more engaged in the searching process when using lesser-known search engines. It appears that branding affects overall Web search at four stages: (a) search engine selection, (b) search engine results page evaluation, (c) individual link evaluation, and (d) evaluation of the landing page. We discuss the implications for search engine marketing and the design of empirical studies measuring search engine performance.

0.0017848461 = product of:
  0.010709076 = sum of:
    0.010709076 = weight(_text_:in in 2091) [ClassicSimilarity], result of:
      0.010709076 = score(doc=2091,freq=8.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.18034597 = fieldWeight in 2091, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=2091)
  0.16666667 = coord(1/6)

Abstract

In this paper, we define and present a comprehensive classification of user intent for Web searching. The classification consists of three hierarchical levels of informational, navigational, and transactional intent. After deriving attributes of each, we then developed a software application that automatically classified queries using a Web search engine log of over a million and a half queries submitted by several hundred thousand users. Our findings show that more than 80% of Web queries are informational in nature, with about 10% each being navigational and transactional. In order to validate the accuracy of our algorithm, we manually coded 400 queries and compared the results from this manual classification to the results determined by the automated method. This comparison showed that the automatic classification has an accuracy of 74%. Of the remaining 25% of the queries, the user intent is vague or multi-faceted, pointing to the need for probabilistic classification. We discuss how search engines can use knowledge of user intent to provide more targeted and relevant results in Web searching.

0.0016629322 = product of:
  0.009977593 = sum of:
    0.009977593 = weight(_text_:in in 3157) [ClassicSimilarity], result of:
      0.009977593 = score(doc=3157,freq=10.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.16802745 = fieldWeight in 3157, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3157)
  0.16666667 = coord(1/6)

Abstract

In this paper we report research results investigating microblogging as a form of electronic word-of-mouth for sharing consumer opinions concerning brands. We analyzed more than 150,000 microblog postings containing branding comments, sentiments, and opinions. We investigated the overall structure of these microblog postings, the types of expressions, and the movement in positive or negative sentiment. We compared automated methods of classifying sentiment in these microblogs with manual coding. Using a case study approach, we analyzed the range, frequency, timing, and content of tweets in a corporate account. Our research findings show that 19% of microblogs contain mention of a brand. Of the branding microblogs, nearly 20% contained some expression of brand sentiments. Of these, more than 50% were positive and 33% were critical of the company or product. Our comparison of automated and manual coding showed no significant differences between the two approaches. In analyzing microblogs for structure and composition, the linguistic structure of tweets approximate the linguistic patterns of natural language expressions. We find that microblogging is an online tool for customer word of mouth communications and discuss the implications for corporations using microblogging as part of their overall marketing strategy.

0.0015457221 = product of:
  0.009274333 = sum of:
    0.009274333 = weight(_text_:in in 983) [ClassicSimilarity], result of:
      0.009274333 = score(doc=983,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1561842 = fieldWeight in 983, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=983)
  0.16666667 = coord(1/6)

Abstract

Ecommerce is developing into a fast-growing channel for new business, so a strong presence in this domain could prove essential to the success of numerous commercial organizations. However, there is little research examining ecommerce at the individual customer level, particularly on the success of everyday ecommerce searches. This is critical for the continued success of online commerce. The purpose of this research is to evaluate the effectiveness of search engines in the retrieval of relevant ecommerce links. The study examines the effectiveness of five different types of search engines in response to ecommerce queries by comparing the engines' quality of ecommerce links using topical relevancy ratings. This research employs 100 ecommerce queries, five major search engines, and more than 3540 Web links. The findings indicate that links retrieved using an ecommerce search engine are significantly better than those obtained from most other engines types but do not significantly differ from links obtained from a Web directory service. We discuss the implications for Web system design and ecommerce marketing campaigns.

0.0015457221 = product of:
  0.009274333 = sum of:
    0.009274333 = weight(_text_:in in 1055) [ClassicSimilarity], result of:
      0.009274333 = score(doc=1055,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1561842 = fieldWeight in 1055, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=1055)
  0.16666667 = coord(1/6)

Abstract

Searchers seldom make use of the advanced searching features that could improve the quality of the search process because they do not know these features exist, do not understand how to use them, or do not believe they are effective or efficient. Information retrieval systems offering automated assistance could greatly improve search effectiveness by suggesting or implementing assistance automatically. A critical issue in designing such systems is determining when the system should intervene in the search process. In this paper, we report the results of an empirical study analyzing when during the search process users seek automated searching assistance from the system and when they implement the assistance. We designed a fully functional, automated assistance application and conducted a study with 30 subjects interacting with the system. The study used a 2G TREC document collection and TREC topics. Approximately 50% of the subjects sought assistance, and over 80% of those implemented that assistance. Results from the evaluation indicate that users are willing to accept automated assistance during the search process, especially after viewing results and locating relevant documents. We discuss implications for interactive information retrieval system design and directions for future research.

0.0015457221 = product of:
  0.009274333 = sum of:
    0.009274333 = weight(_text_:in in 2033) [ClassicSimilarity], result of:
      0.009274333 = score(doc=2033,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1561842 = fieldWeight in 2033, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=2033)
  0.16666667 = coord(1/6)

Abstract

Collaborative information behavior is an essential aspect of organizational work; however, we have very limited understanding of this behavior. Most models of information behavior focus on the individual seeker of information. In this paper, we report the results from two empirical studies that investigate aspects of collaborative information behavior in organizational settings. From these studies, we found that collaborative information behavior differs from individual information behavior with respect to how individuals interact with each other, the complexity of the information need, and the role of information technology. There are specific triggers for transitioning from individual to collaborative information behavior, including lack of domain expertise. The information retrieval technologies used affect collaborative information behavior by acting as important supporting mechanisms. From these results and prior work, we develop a model of collaborative information behavior along the axes of participant behavior, situational elements, and contextual triggers. We also present characteristics of collaborative information system including search, chat, and sharing. We discuss implications for the design of collaborative information retrieval systems and directions for future work.

0.0015457221 = product of:
  0.009274333 = sum of:
    0.009274333 = weight(_text_:in in 3690) [ClassicSimilarity], result of:
      0.009274333 = score(doc=3690,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1561842 = fieldWeight in 3690, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=3690)
  0.16666667 = coord(1/6)

Abstract

In this article, we identify, compare, and contrast theoretical constructs for the fields of information searching and information retrieval to emphasize the uniqueness of and synergy between the fields. Theoretical constructs are the foundational elements that underpin a field's core theories, models, assumptions, methodologies, and evaluation metrics. We provide a framework to compare and contrast the theoretical constructs in the fields of information searching and information retrieval using intellectual perspective and theoretical orientation. The intellectual perspectives are information searching, information retrieval, and cross-cutting; and the theoretical orientations are information, people, and technology. Using this framework, we identify 17 significant constructs in these fields contrasting the differences and comparing the similarities. We discuss the impact of the interplay among these constructs for moving research forward within both fields. Although there is tension between the fields due to contradictory constructs, an examination shows a trend toward convergence. We discuss the implications for future research within the information searching and information retrieval fields.

0.0014873719 = product of:
  0.008924231 = sum of:
    0.008924231 = weight(_text_:in in 216) [ClassicSimilarity], result of:
      0.008924231 = score(doc=216,freq=8.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.15028831 = fieldWeight in 216, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=216)
  0.16666667 = coord(1/6)

Abstract

The application of clustering to Web search engine technology is a novel approach that offers structure to the information deluge often faced by Web searchers. Clustering methods have been well studied in research labs; however, real user searching with clustering systems in operational Web environments is not well understood. This article reports on results from a transaction log analysis of Vivisimo.com, which is a Web meta-search engine that dynamically clusters users' search results. A transaction log analysis was conducted on 2-week's worth of data collected from March 28 to April 4 and April 25 to May 2, 2004, representing 100% of site traffic during these periods and 2,029,734 queries overall. The results show that the highest percentage of queries contained two terms. The highest percentage of search sessions contained one query and was less than 1 minute in duration. Almost half of user interactions with clusters consisted of displaying a cluster's result set, and a small percentage of interactions showed cluster tree expansion. Findings show that 11.1% of search sessions were multitasking searches, and there are a broad variety of search topics in multitasking search sessions. Other searching interactions and statistics on repeat users of the search engine are reported. These results provide insights into search characteristics with a cluster-based Web search engine and extend research into Web searching trends.

0.0014873719 = product of:
  0.008924231 = sum of:
    0.008924231 = weight(_text_:in in 285) [ClassicSimilarity], result of:
      0.008924231 = score(doc=285,freq=8.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.15028831 = fieldWeight in 285, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=285)
  0.16666667 = coord(1/6)

Abstract

Detecting query reformulations within a session by a Web searcher is an important area of research for designing more helpful searching systems and targeting content to particular users. Methods explored by other researchers include both qualitative (i.e., the use of human judges to manually analyze query patterns on usually small samples) and nondeterministic algorithms, typically using large amounts of training data to predict query modification during sessions. In this article, we explore three alternative methods for detection of session boundaries. All three methods are computationally straightforward and therefore easily implemented for detection of session changes. We examine 2,465,145 interactions from 534,507 users of Dogpile.com on May 6, 2005. We compare session analysis using (a) Internet Protocol address and cookie; (b) Internet Protocol address, cookie, and a temporal limit on intrasession interactions; and (c) Internet Protocol address, cookie, and query reformulation patterns. Overall, our analysis shows that defining sessions by query reformulation along with Internet Protocol address and cookie provides the best measure, resulting in an 82% increase in the count of sessions. Regardless of the method used, the mean session length was fewer than three queries, and the mean session duration was less than 30 min. Searchers most often modified their query by changing query terms (nearly 23% of all query modifications) rather than adding or deleting terms. Implications are that for measuring searching traffic, unique sessions may be a better indicator than the common metric of unique visitors. This research also sheds light on the more complex aspects of Web searching involving query modifications and may lead to advances in searching tools.

0.0014873719 = product of:
  0.008924231 = sum of:
    0.008924231 = weight(_text_:in in 968) [ClassicSimilarity], result of:
      0.008924231 = score(doc=968,freq=8.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.15028831 = fieldWeight in 968, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=968)
  0.16666667 = coord(1/6)

Abstract

The Web and especially major Web search engines are essential tools in the quest to locate online information for many people. This paper reports results from research that examines characteristics and changes in Web searching from nine studies of five Web search engines based in the US and Europe. We compare interactions occurring between users and Web search engines from the perspectives of session length, query length, query complexity, and content viewed among the Web search engines. The results of our research shows (1) users are viewing fewer result pages, (2) searchers on US-based Web search engines use more query operators than searchers on European-based search engines, (3) there are statistically significant differences in the use of Boolean operators and result pages viewed, and (4) one cannot necessary apply results from studies of one particular Web search engine to another Web search engine. The wide spread use of Web search engines, employment of simple queries, and decreased viewing of result pages may have resulted from algorithmic enhancements by Web search engine companies. We discuss the implications of the findings for the development of Web search engines and design of online content.

0.0014873719 = product of:
  0.008924231 = sum of:
    0.008924231 = weight(_text_:in in 1015) [ClassicSimilarity], result of:
      0.008924231 = score(doc=1015,freq=8.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.15028831 = fieldWeight in 1015, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1015)
  0.16666667 = coord(1/6)

Abstract

The Web has become a worldwide source of information and a mainstream business tool. It is changing the way people conduct the daily business of their lives. As these changes are occurring, we need to understand what Web searching trends are emerging within the various global regions. What are the regional differences and trends in Web searching, if any? What is the effectiveness of Web search engines as providers of information? As part of a body of research studying these questions, we have analyzed two data sets collected from queries by mainly European users submitted to AlltheWeb.com on 6 February 2001 and 28 May 2002. AlltheWeb.com is a major and highly rated European search engine. Each data set contains approximately a million queries submitted by over 200,000 users and spans a 24-h period. This longitudinal benchmark study shows that European Web searching is evolving in certain directions. There was some decline in query length, with extremely simple queries. European search topics are broadening, with a notable percentage decline in sexual and pornographic searching. The majority of Web searchers view fewer than five Web documents, spending only seconds on a Web document. Approximately 50% of the Web documents viewed by these European users were topically relevant. We discuss the implications for Web information systems and information content providers.

0.0014873719 = product of:
  0.008924231 = sum of:
    0.008924231 = weight(_text_:in in 4223) [ClassicSimilarity], result of:
      0.008924231 = score(doc=4223,freq=8.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.15028831 = fieldWeight in 4223, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4223)
  0.16666667 = coord(1/6)

Abstract

In this research, we investigated whether a learning process has unique information searching characteristics. The results of this research show that information searching is a learning process with unique searching characteristics specific to particular learning levels. In a laboratory experiment, we studied the searching characteristics of 72 participants engaged in 426 searching tasks. We classified the searching tasks according to Anderson and Krathwohl's taxonomy of the cognitive learning domain. Research results indicate that applying and analyzing, the middle two of the six categories, generally take the most searching effort in terms of queries per session, topics searched per session, and total time searching. Interestingly, the lowest two learning categories, remembering and understanding, exhibit searching characteristics similar to the highest order learning categories of evaluating and creating. Our results suggest the view of Web searchers having simple information needs may be incorrect. Instead, we discovered that users applied simple searching expressions to support their higher-level information needs. It appears that searchers rely primarily on their internal knowledge for evaluating and creating information needs, using search primarily for fact checking and verification. Overall, results indicate that a learning theory may better describe the information searching process than more commonly used paradigms of decision making or problem solving. The learning style of the searcher does have some moderating effect on exhibited searching characteristics. The implication of this research is that rather than solely addressing a searcher's expressed information need, searching systems can also address the underlying learning need of the user.

0.0014873719 = product of:
  0.008924231 = sum of:
    0.008924231 = weight(_text_:in in 3345) [ClassicSimilarity], result of:
      0.008924231 = score(doc=3345,freq=8.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.15028831 = fieldWeight in 3345, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3345)
  0.16666667 = coord(1/6)

Abstract

Many people turn to their social networks to find information through the practice of question and answering. We believe it is necessary to use different answering strategies based on the type of questions to accommodate the different information needs. In this research, we propose the ASK taxonomy that categorizes questions posted on social networking sites into three types according to the nature of the questioner's inquiry of accuracy, social, or knowledge. To automatically decide which answering strategy to use, we develop a predictive model based on ASK question types using question features from the perspectives of lexical, topical, contextual, and syntactic as well as answer features. By applying the classifier on an annotated data set, we present a comprehensive analysis to compare questions in terms of their word usage, topical interests, temporal and spatial restrictions, syntactic structure, and response characteristics. Our research results show that the three types of questions exhibited different characteristics in the way they are asked. Our automatic classification algorithm achieves an 83% correct labeling result, showing the value of the ASK taxonomy for the design of social question and answering systems.

0.0014573209 = product of:
  0.008743925 = sum of:
    0.008743925 = weight(_text_:in in 993) [ClassicSimilarity], result of:
      0.008743925 = score(doc=993,freq=12.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.14725187 = fieldWeight in 993, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.03125 = fieldNorm(doc=993)
  0.16666667 = coord(1/6)

Abstract

The performance and capabilities of Web search engines is an important and significant area of research. Millions of people world wide use Web search engines very day. This paper reports the results of a major study examining the overlap among results retrieved by multiple Web search engines for a large set of more than 10,000 queries. Previous smaller studies have discussed a lack of overlap in results returned by Web search engines for the same queries. The goal of the current study was to conduct a large-scale study to measure the overlap of search results on the first result page (both non-sponsored and sponsored) across the four most popular Web search engines, at specific points in time using a large number of queries. The Web search engines included in the study were MSN Search, Google, Yahoo! and Ask Jeeves. Our study then compares these results with the first page results retrieved for the same queries by the metasearch engine Dogpile.com. Two sets of randomly selected user-entered queries, one set was 10,316 queries and the other 12,570 queries, from Infospace's Dogpile.com search engine (the first set was from Dogpile, the second was from across the Infospace Network of search properties were submitted to the four single Web search engines). Findings show that the percent of total results unique to only one of the four Web search engines was 84.9%, shared by two of the three Web search engines was 11.4%, shared by three of the Web search engines was 2.6%, and shared by all four Web search engines was 1.1%. This small degree of overlap shows the significant difference in the way major Web search engines retrieve and rank results in response to given queries. Results point to the value of metasearch engines in Web retrieval to overcome the biases of individual search engines.

0.0012881019 = product of:
  0.007728611 = sum of:
    0.007728611 = weight(_text_:in in 4815) [ClassicSimilarity], result of:
      0.007728611 = score(doc=4815,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1301535 = fieldWeight in 4815, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4815)
  0.16666667 = coord(1/6)

Abstract

We report quantitative and qualitative results of an empirical evaluation to determine whether automated assistance improves searching performance and when searchers desire system intervention in the search process. Forty participants interacted with two fully functional information retrieval systems in a counterbalanced, within-participant study. The systems were identical in all respects except that one offered automated assistance and the other did not. The study used a client-side automated assistance application, an approximately 500,000-document Text REtrieval Conference content collection, and six topics. Results indicate that automated assistance can improve searching performance. However, the improvement is less dramatic than one might expect, with an approximately 20% performance increase, as measured by the number of userselected relevant documents. Concerning patterns of interaction, we identified 1,879 occurrences of searchersystem interactions and classified them into 9 major categories and 27 subcategories or states. Results indicate that there are predictable patterns of times when searchers desire and implement searching assistance. The most common three-state pattern is Execute Query-View Results: With Scrolling-View Assistance. Searchers appear receptive to automated assistance; there is a 71% implementation rate. There does not seem to be a correlation between the use of assistance and previous searching performance. We discuss the implications for the design of information retrieval systems and future research directions.