Search (27 results, page 2 of 2)

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Abstract

University libraries provide access to thousands of journals and spend millions of dollars annually on electronic resources. With several commercial entities providing these electronic resources, the result can be silo systems and processes to evaluate cost and usage of these resources, making it difficult to provide meaningful analytics. In this research, we examine a subset of journals from a large research library using a web analytics approach with the goal of developing a framework for the analysis of library subscriptions. This foundational approach is implemented by comparing the impact to the cost, titles, and usage for the subset of journals and by assessing the funding area. Overall, the results highlight the benefit of a web analytics evaluation framework for university libraries and the impact of classifying titles based on the funding area. Furthermore, they show the statistical difference in both use and cost among the various funding areas when ranked by cost, eliminating the outliers of heavily used and highly expensive journals. Future work includes refining this model for a larger scale analysis tying metrics to library organizational objectives and for the creation of an online application to automate this analysis.

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Footnote

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.
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."

LCSH

Web usage mining

RSWK

World Wide Web / Suchmaschine

Subject

World Wide Web / Suchmaschine
Web usage mining

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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.

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Abstract

We analyze the transitions from external search, searching on web search engines, to internal search, searching on websites. We categorize 295,571 search episodes composed of a query submitted to web search engines and the subsequent queries submitted to a single website search by the same users. There are a total of 1,136,390 queries from all searches, of which 295,571 are external search queries and 840,819 are internal search queries. We algorithmically classify queries into states and then use n-grams to categorize search patterns. We cluster the searching episodes into major patterns and identify the most commonly occurring, which are: (1) Explorers (43% of all patterns) with a broad external search query and then broad internal search queries, (2) Navigators (15%) with an external search query containing a URL component and then specific internal search queries, and (3) Shifters (15%) with a different, seemingly unrelated, query types when transitioning from external to internal search. The implications of this research are that external search and internal search sessions are part of a single search episode and that online businesses can leverage these search episodes to more effectively target potential customers.

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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.

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Abstract

University libraries provide access to thousands of online journals and other content, spending millions of dollars annually on these electronic resources. Providing access to these online resources is costly, and it is difficult both to analyze the value of this content to the institution and to discern those journals that comparatively provide more value. In this research, we examine 1,510 journals from a large research university library, representing more than 40% of the university's annual subscription cost for electronic resources at the time of the study. We utilize a web analytics approach for the creation of a linear regression model to predict usage among these journals. We categorize metrics into two classes: global (journal focused) and local (institution dependent). Using 275 journals for our training set, our analysis shows that a combination of global and local metrics creates the strongest model for predicting full-text downloads. Our linear regression model has an accuracy of more than 80% in predicting downloads for the 1,235 journals in our test set. The implications of the findings are that university libraries that use local metrics have better insight into the value of a journal and therefore more efficient cost content management.