Search (284 results, page 14 of 15)

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Abstract

Information extraction systems discover structured information in natural language text. Having information in structured form enables much richer querying and data mining than possible over the natural language text. However, information extraction is a computationally expensive task, and hence improving the efficiency of the extraction process over large text collections is of critical interest. In this paper, we focus on an especially valuable family of text collections, namely, the so-called deep-web text collections, whose contents are not crawlable and are only available via querying. Important steps for efficient information extraction over deep-web text collections (e.g., selecting the collections on which to focus the extraction effort, based on their contents; or learning which documents within these collections-and in which order-to process, based on their words and phrases) require having a representative document sample from each collection. These document samples have to be collected by querying the deep-web text collections, an expensive process that renders impractical the existing sampling approaches developed for other data scenarios. In this paper, we systematically study the space of query-based document sampling techniques for information extraction over the deep web. Specifically, we consider (i) alternative query execution schedules, which vary on how they account for the query effectiveness, and (ii) alternative document retrieval and processing schedules, which vary on how they distribute the extraction effort over documents. We report the results of the first large-scale experimental evaluation of sampling techniques for information extraction over the deep web. Our results show the merits and limitations of the alternative query execution and document retrieval and processing strategies, and provide a roadmap for addressing this critically important building block for efficient, scalable information extraction.

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Abstract

Journalists were chosen for study because it was felt that they would be, as information seekers and packagers par excellence, in the advanced guard of Internet users and setting the pace. As it turned out this was not to be case. Despite what appear to be the considerable and direct benefits for them, after having interviewed approximately 150 journalists and observed the action in a variety of news rooms, it appears that less than one in five national journalist use the Internet and the proportion is much less than that for regional journalists. If this poor Internet take up in the workplace was unexpected, another surprise is the characteristics of those who have actually taken the Internet route. Far from being the stereotypical young and male, most are well practised journalist into their thirties/forties, which, of course, runs counter to all that we have been led to believe. Surprisingly, the study showed as much, if not more, interest in using the Internet from the supposedly `busy' senior managers and editors than in the rank and file.

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Abstract

Conventional wisdom holds that queries to information retrieval systems will yield more relevant results if they contain multiple topic-related terms and use Boolean and phrase operators to enhance interpretation. Although studies have shown that the users of Web-based search engines typically enter short, term-based queries and rarely use search operators, little information exists concerning the effects of term and operator usage on the relevancy of search results. In this study, search engine users formulated queries on eight search topics. Each query was submitted to the user-specified search engine, and relevancy ratings for the retrieved pages were assigned. Expert-formulated queries were also submitted and provided a basis for comparing relevancy ratings across search engines. Data analysis based on our research model of the term and operator factors affecting relevancy was then conducted. The results show that the difference in the number of terms between expert and nonexpert searches, the percentage of matching terms between those searches, and the erroneous use of nonsupported operators in nonexpert searches explain most of the variation in the relevancy of search results. These findings highlight the need for designing search engine interfaces that provide greater support in the areas of term selection and operator usage

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Abstract

Although many studies have identified search tactics, few studies have explored tactic transitions. This study investigated the transitions of search tactics during the Web-based search process. Bringing their own 60 search tasks, 31 participants, representing the general public with different demographic characteristics, participated in the study. Data collected from search logs and verbal protocols were analyzed by applying both qualitative and quantitative methods. The findings of this study show that participants exhibited some unique Web search tactics. They overwhelmingly employed accessing and evaluating tactics; they used fewer tactics related to modifying search statements, monitoring the search process, organizing search results, and learning system features. The contributing factors behind applying most and least frequently employed search tactics are in relation to users' efforts, trust in information retrieval (IR) systems, preference, experience, and knowledge as well as limitation of the system design. A matrix of search-tactic transitions was created to show the probabilities of transitions from one tactic to another. By applying fifth-order Markov chain, the results also presented the most common search strategies representing patterns of tactic transition occurring at the beginning, middle, and ending phases within one search session. The results of this study generated detailed and useful guidance for IR system design to support the most frequently applied tactics and transitions, to reduce unnecessary transitions, and support transitions at different phases.

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Abstract

As information becomes more ubiquitous and the demands that searchers have on search systems grow, there is a need to support search behaviors beyond simple lookup. Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Exploratory search describes an information-seeking problem context that is open-ended, persistent, and multifaceted, and information-seeking processes that are opportunistic, iterative, and multitactical. Exploratory searchers aim to solve complex problems and develop enhanced mental capacities. Exploratory search systems support this through symbiotic human-machine relationships that provide guidance in exploring unfamiliar information landscapes. Exploratory search has gained prominence in recent years. There is an increased interest from the information retrieval, information science, and human-computer interaction communities in moving beyond the traditional turn-taking interaction model supported by major Web search engines, and toward support for human intelligence amplification and information use. In this lecture, we introduce exploratory search, relate it to relevant extant research, outline the features of exploratory search systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratory search. Exploratory search is a new frontier in the search domain and is becoming increasingly important in shaping our future world.

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Abstract

Both user involvement and system support play important roles in applying search tactics. To apply search tactics in the information retrieval (IR) processes, users make decisions and take actions in the search process, while IR systems assist them by providing different system features. After analyzing 61 participants' information searching diaries and questionnaires we identified various types of user involvement and system support in applying different types of search tactics. Based on quantitative analysis, search tactics were classified into 3 groups: user-dominated, system-dominated, and balanced tactics. We further explored types of user involvement and types of system support in applying search tactics from the 3 groups. The findings show that users and systems play major roles in applying user-dominated and system-dominated tactics, respectively. When applying balanced tactics, users and systems must collaborate closely with each other. In this article, we propose a model that illustrates user involvement and system support as they occur in user-dominated tactics, system-dominated tactics, and balanced tactics. Most important, IR system design implications are discussed to facilitate effective and efficient applications of the 3 groups of search tactics.

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Abstract

This article investigates how to improve the effectiveness of voice search systems. Earlier research found that participants employed voice search much less frequently than keyboard search. The main reasons that participants disliked voice search are system mistakes and the inability to modify queries. In keyboard search, query reformulation is facilitated by partial query modification, which is not supported by most of the current voice search systems. Consequently, users need to speak the complete query in voice search even with only minor changes. This article focuses on examining partial query modification during voice search through a Wizard of Oz user experiment. It examines if users would prefer partial query modification and how they perform it in voice search. Thirty-two participants participated in the experiment. Results indicated that when given the opportunity, the users performed more partial query modifications than complete queries. Common partial query modification strategies and patterns emerged from the experiment. The results can be used to improve the voice search system design and benefit the research community in general. System implications and future work were discussed.

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Abstract

In using the Internet to solve everyday problems, older adults tend to find fewer correct answers compared to younger adults. Some authors have argued that these differences could be explained by age-related decline. The present study aimed to analyze the relationship between web-searching navigation and users' age, considering the Intelligence Quotient (IQ) and frequency of Internet and personal computer use. The intent was to identify differences due to age and not to other variables (that is, cognitive decline, expertise with the tool). Eighteen students (18-30?years) and 18 older adults (60-75?years) took part in the experiment. Inclusion criteria were the frequent use of computers and a web-searching activity; the older adults performed the Mini-Mental State Examination to exclude cognitive impairment. Participants were requested to perform the Kaufman Brief Intelligence Test 2nd ed. to measure their IQ level, and nine everyday web-searching tasks of differing complexity. The results showed that older participants spent more time on solving tasks than younger participants, but with the same accuracy as young people. Furthermore, nonverbal IQ improved performance in terms of time among the older participants. Age did not influence web-searching behavior in users with normal expertise and intelligence.

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Abstract

In information seeking and retrieval research, researchers often collect data about users' behaviors to predict task characteristics and personalize information for users. The reliability of user behavior may be directly influenced by data collection methods. This article reports on a mixed-methods study examining the impact of study setting (laboratory setting vs. remote setting) and task authenticity (authentic task vs. simulated task) on users' online browsing and searching behaviors. Thirty-six undergraduate participants finished one lab session and one remote session in which they completed one authentic and one simulated task. Using log data collected from 144 task sessions, this study demonstrates that the synthetic lab study setting and simulated tasks had significant influences mostly on behaviors related to content pages (e.g., page dwell time, number of pages visited per task). Meanwhile, first-query behaviors were less affected by study settings or task authenticity than whole-session behaviors, indicating the reliability of using first-query behaviors in task prediction. Qualitative interviews reveal why users were influenced. This study addresses methodological limitations in existing research and provides new insights and implications for researchers who collect online user search behavioral data.

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Abstract

How do you find your way in an age of information overload? How can you filter streams of complex information to pull out only what you want? Why does it matter how information is structured when Google seems to magically bring up the right answer to your questions? What does it mean to be "findable" in this day and age? This eye-opening new book examines the convergence of information and connectivity. Written by Peter Morville, author of the groundbreakin Information Architecture for the World Wide Web, the book defines our current age as a state of unlimited findability. In other words, anyone can find anything at any time. Complete navigability. Morville discusses the Internet, GIS, and other network technologies that are coming together to make unlimited findability possible. He explores how the melding of these innovations impacts society, since Web access is now a standard requirement for successful people and businesses. But before he does that, Morville looks back at the history of wayfinding and human evolution, suggesting that our fear of being lost has driven us to create maps, charts, and now, the mobile Internet.
The book's central thesis is that information literacy, information architecture, and usability are all critical components of this new world order. Hand in hand with that is the contention that only by planning and designing the best possible software, devices, and Internet, will we be able to maintain this connectivity in the future. Morville's book is highlighted with full color illustrations and rich examples that bring his prose to life. Ambient Findability doesn't preach or pretend to know all the answers. Instead, it presents research, stories, and examples in support of its novel ideas. Are w truly at a critical point in our evolution where the quality of our digital networks will dictate how we behave as a species? Is findability indeed the primary key to a successful global marketplace in the 21st century and beyond. Peter Morville takes you on a thought-provoking tour of these memes and more -- ideas that will not only fascinate but will stir your creativity in practical ways that you can apply to your work immediately.

Footnote

Das zweite Kapitel ("A Brief History of Wayfinding") beschreibt, wie Menschen sich in Umgebungen zurechtfinden. Dies ist insofern interessant, als hier nicht erst bei Informationssystemen oder dem WWW begonnen wird, sondern allgemeine Erkenntnisse beispielsweise über die Orientierung in natürlichen Umgebungen präsentiert werden. Viele typische Verhaltensweisen der Nutzer von Informationssystemen können so erklärt werden. So interessant dieses Thema allerdings ist, wirkt das Kapitel leider doch nur wie eine Zusammenstellung von Informationen aus zweiter Hand. Offensichtlich ist, dass Morville nicht selbst an diesen Themen geforscht hat, sondern die Ergebnisse (wenn auch auf ansprechende Weise) zusammengeschrieben hat. Dieser Eindruck bestätigt sich auch in weiteren Kapiteln: Ein flüssig geschriebener Text, der es jedoch an einigen Stellen an Substanz fehlen lässt. Kapitel drei, "Information Interaction" beginnt mit einem Rückgriff auf Calvin Mooers zentrale Aussage aus dem Jahre 1959: "An information retrieval system will tend not to be used whenever it is more painful and troublesome for a customer to have information than for him not to have it." In der Tat sollte man sich dies bei der Erstellung von Informationssystemen immer vergegenwärtigen; die Reihe der Systeme, die gerade an dieser Hürde gescheitert sind, ist lang. Das weitere Kapitel führt in einige zentrale Konzepte der Informationswissenschaft (Definition des Begriffs Information, Erläuterung des Information Retrieval, Wissensrepräsentation, Information Seeking Behaviour) ein, allerdings ohne jeden Anspruch auf Vollständigkeit. Es wirkt vielmehr so, dass der Autor sich die gerade für sein Anliegen passenden Konzepte auswählt und konkurrierende Ansätze beiseite lässt. Nur ein Beispiel: Im Abschnitt "Information Interaction" wird relativ ausführlich das Konzept des Berrypicking nach Marcia J. Bates präsentiert, allerdings wird es geradezu als exklusiv verkauft, was es natürlich bei weitem nicht ist. Natürlich kann es nicht Aufgabe dieses Buchs sein, einen vollständigen Überblick über alle Theorien des menschlichen Suchverhaltens zu geben (dies ist an anderer Stelle vorbildlich geleistet worden'), aber doch wenigstens der Hinweis auf einige zentrale Ansätze wäre angebracht gewesen. Spätestens in diesem Kapitel wird klar, dass das Buch sich definitiv nicht an Informationswissenschaftler wendet, die auf der einen Seite mit den grundlegenden Themen vertraut sein dürften, andererseits ein wenig mehr Tiefgang erwarten würden. Also stellt sich die Frage - und diese ist zentral für die Bewertung des gesamten Werks.

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