Search (33 results, page 2 of 2)

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Abstract

Limited research has investigated the role of multitasking, cognitive coordination, and cognitive shifts during web search. Understanding these three behaviors is crucial to web search model development. This study aims to explore characteristics of multitasking behavior, types of cognitive shifts, and levels of cognitive coordination as well as the relationship between them during web search. Data collection included pre- and postquestionnaires, think-aloud protocols, web search logs, observations, and interviews with 42 graduate students who conducted 315 web search sessions with 221 information problems. Results show that web search is a dynamic interaction including the ordering of multiple information problems and the generation of evolving information problems, including task switching, multitasking, explicit task and implicit mental coordination, and cognitive shifting. Findings show that explicit task-level coordination is closely linked to multitasking, and implicit cognitive-level coordination is related to the task-coordination process; including information problem development and task switching. Coordination mechanisms directly result in cognitive state shifts including strategy, evaluation, and view states that affect users' holistic shifts in information problem understanding and knowledge contribution. A web search model integrating multitasking, cognitive coordination, and cognitive shifts (MCC model) is presented. Implications and further research also are discussed.

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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.

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Abstract

Web queries in question format are becoming a common element of a user's interaction with Web search engines. Web search services such as Ask Jeeves - a publicly accessible question and answer (Q&A) search engine - request users to enter question format queries. This paper provides results from a study examining queries in question format submitted to two different Web search engines - Ask Jeeves that explicitly encourages queries in question format and the Excite search service that does not explicitly encourage queries in question format. We identify the characteristics of queries in question format in two different data sets: (1) 30,000 Ask Jeeves queries and 15,575 Excite queries, including the nature, length, and structure of queries in question format. Findings include: (1) 50% of Ask Jeeves queries and less than 1% of Excite were in question format, (2) most users entered only one query in question format with little query reformulation, (3) limited range of formats for queries in question format - mainly "where", "what", or "how" questions, (4) most common question query format was "Where can I find ..." for general information on a topic, and (5) non-question queries may be in request format. Overall, four types of user Web queries were identified: keyword, Boolean, question, and request. These findings provide an initial mapping of the structure and content of queries in question and request format. Implications for Web search services are discussed.

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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.

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Abstract

Multitasking is the human ability to handle the demands of multiple tasks. Multitasking behavior involves the ordering of multiple tasks and switching between tasks. People often multitask when using information retrieval (IR) technologies as they seek information on more than one information problem over single or multiple search episodes. However, limited studies have examined how people order their information problems, especially during their Web search engine interaction. The aim of our exploratory study was to investigate assigned information problem ordering by forty (40) study participants engaged in Web search. Findings suggest that assigned information problem ordering was influenced by the following factors, including personal interest, problem knowledge, perceived level of information available on the Web, ease of finding information, level of importance and seeking information on information problems in order from general to specific. Personal interest and problem knowledge were the major factors during assigned information problem ordering. Implications of the findings and further research are discussed. The relationship between information problem ordering and gratification theory is an important area for further exploration.

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Abstract

Query reformulation is a key user behavior during Web search. Our research goal is to develop predictive models of query reformulation during Web searching. This article reports results from a study in which we automatically classified the query-reformulation patterns for 964,780 Web searching sessions, composed of 1,523,072 queries, to predict the next query reformulation. We employed an n-gram modeling approach to describe the probability of users transitioning from one query-reformulation state to another to predict their next state. We developed first-, second-, third-, and fourth-order models and evaluated each model for accuracy of prediction, coverage of the dataset, and complexity of the possible pattern set. The results show that Reformulation and Assistance account for approximately 45% of all query reformulations; furthermore, the results demonstrate that the first- and second-order models provide the best predictability, between 28 and 40% overall and higher than 70% for some patterns. Implications are that the n-gram approach can be used for improving searching systems and searching assistance.

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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.

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Abstract

Recent studies show that humans engage in multitasking information behaviors, often in libraries, as they seek and search for information on more than one information task. Multitasking information behaviors may consist of library search and use behaviors, or database or Web search sessions on multiple information tasks. However, few human information behavior models of seeking, searching or use, or library use models, include considerations of multitasking information behavior. This paper reports results from a case study exploring multitasking information behavior by an information seeker in a public library using diary, observation and interview data collection techniques. The information seeker sought information on four unrelated personal information tasks during two public library visits. Findings include a taxonomy of information behaviors; a sequential flowchart of the information seeker's complex and iterative processes, including multitasking information behavior, electronic searches, physical library searches, serendipitous browsing, and successive searches; and that the information seeker engaged in a process of 17 information task switches over two library visits. A model of information multitasking and information task switching is presented. Implications for library services and bibliographic instruction are also discussed.

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Abstract

Search engines fail to make a clear distinction between items of varying relevance when presenting search results to users. Instead, they rely on the user of the system to estimate which items are relevant, partially relevant, or not relevant. The user of the system is given the task of distinguishing between documents that are relevant to different degrees. This process often hinders the accessibility of relevant or partially relevant documents, particularly when the results set is large and documents of varying relevance are scattered throughout the set. In this paper, we present a clustering scheme that groups documents within relevant, partially relevant, and not relevant regions for a given search. A clustering algorithm accomplishes the task of clustering documents based on relevance. The clusters were evaluated by end-users issuing categorical, interval, and descriptive relevance judgments for the documents returned from a search. The degree of overlap between users and the system for each of the clustered regions was measured to determine the overall effectiveness of the algorithm. This research showed that clustering documents on the Web by regions of relevance is highly necessary and quite feasible.

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Abstract

Humans have used electronic information retrieval (IR) systems for more than 50 years as they evolved from experimental systems to full-scale Web search engines and digital libraries. The fields of library and information science (LIS), cognitive science, human factors and computer science have historically been the leading disciplines in conducting research that seeks to model human interaction with IR systems for all kinds of information related behaviors. As technology problems have been mastered, the theoretical and applied framework for studying human interaction with IR systems has evolved from systems-centered to more user-centered, or cognitive-centered approaches. However, cognitive information retrieval (CIR) research that focuses on user interaction with IR systems is still largely under-funded and is often not included at computing and systems design oriented conferences. But CIR-focused research continues, and there are signs that some IR systems designers in academia and the Web search business are realizing that user behavior research can provide valuable insights into systems design and evaluation. The goal of our book is to provide an overview of new CIR research directions. This book does not provide a history of the research field of CIR. Instead, the book confronts new ways of looking at the human information condition with regard to our increasing need to interact with IR systems. The need has grown due to a number of factors, including the increased importance of information to more people in this information age. Also, IR was once considered document-oriented, but has now evolved to include multimedia, text, and other information objects. As a result, IR systems and their complexity have proliferated as users and user purposes for using them have also proliferated. Human interaction with IR systems can often be frustrating as people often lack an understanding of IR system functionality.

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Abstract

As digital libraries become a major source of information for many people, we need to know more about how people seek and retrieve information in digital environments. Quite commonly, users with a problem-at-hand and associated question-in-mind repeatedly search a literature for answers, and seek information in stages over extended periods from a variety of digital information resources. The process of repeatedly searching over time in relation to a specific, but possibly an evolving information problem (including changes or shifts in a variety of variables), is called the successive search phenomenon. The study outlined in this paper is currently investigating this new and little explored line of inquiry for information retrieval, Web searching, and digital libraries. The purpose of the research project is to investigate the nature, manifestations, and behavior of successive searching by users in digital environments, and to derive criteria for use in the design of information retrieval interfaces and systems supporting successive searching behavior. This study includes two related projects. The first project is based in the School of Library and Information Sciences at the University of North Texas and is funded by a National Science Foundation POWRE Grant <http://www.nsf.gov/cgi-bin/show?award=9753277>. The second project is based at the Department of Information Studies at the University of Sheffield (UK) and is funded by a grant from the British Library <http://www.shef. ac.uk/~is/research/imrg/uncerty.html> Research and Innovation Center. The broad objectives of each project are to examine the nature and extent of successive search episodes in digital environments by real users over time. The specific aim of the current project is twofold: * To characterize progressive changes and shifts that occur in: user situational context; user information problem; uncertainty reduction; user cognitive styles; cognitive and affective states of the user, and consequently in their queries; and * To characterize related changes over time in the type and use of information resources and search strategies particularly related to given capabilities of IR systems, and IR search engines, and examine changes in users' relevance judgments and criteria, and characterize their differences. The study is an observational, longitudinal data collection in the U.S. and U.K. Three questionnaires are used to collect data: reference, client post search and searcher post search questionnaires. Each successive search episode with a search intermediary for textual materials on the DIALOG Information Service is audiotaped and search transaction logs are recorded. Quantitative analysis includes statistical analysis using Likert scale data from the questionnaires and log-linear analysis of sequential data. Qualitative methods include: content analysis, structuring taxonomies; and diagrams to describe shifts and transitions within and between each search episode. Outcomes of the study are the development of appropriate model(s) for IR interactions in successive search episodes and the derivation of a set of design criteria for interfaces and systems supporting successive searching.