Search (31 results, page 2 of 2)

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Abstract

Metasearch engines are an intuitive method for improving the performance of Web search by increasing coverage, returning large numbers of results with a focus on relevance, and presenting alternative views of information needs. However, the use of metasearch engines in an operational environment is not well understood. In this study, we investigate the usage of Dogpile.com, a major Web metasearch engine, with the aim of discovering how Web searchers interact with metasearch engines. We report results examining 2,465,145 interactions from 534,507 users of Dogpile.com on May 6, 2005 and compare these results with findings from other Web searching studies. We collect data on geographical location of searchers, use of system feedback, content selection, sessions, queries, and term usage. Findings show that Dogpile.com searchers are mainly from the USA (84% of searchers), use about 3 terms per query (mean = 2.85), implement system feedback moderately (8.4% of users), and generally (56% of users) spend less than one minute interacting with the Web search engine. Overall, metasearchers seem to have higher degrees of interaction than searchers on non-metasearch engines, but their sessions are for a shorter period of time. These aspects of metasearching may be what define the differences from other forms of Web searching. We discuss the implications of our findings in relation to metasearch for Web searchers, search engines, and content providers.

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Abstract

A user's single session with a Web search engine or information retrieval (IR) system may consist of seeking information on single or multiple topics, and switch between tasks or multitasking information behavior. Most Web search sessions consist of two queries of approximately two words. However, some Web search sessions consist of three or more queries. We present findings from two studies. First, a study of two-query search sessions on the AltaVista Web search engine, and second, a study of three or more query search sessions on the AltaVista Web search engine. We examine the degree of multitasking search and information task switching during these two sets of AltaVista Web search sessions. A sample of two-query and three or more query sessions were filtered from AltaVista transaction logs from 2002 and qualitatively analyzed. Sessions ranged in duration from less than a minute to a few hours. Findings include: (1) 81% of two-query sessions included multiple topics, (2) 91.3% of three or more query sessions included multiple topics, (3) there are a broad variety of topics in multitasking search sessions, and (4) three or more query sessions sometimes contained frequent topic changes. Multitasking is found to be a growing element in Web searching. This paper proposes an approach to interactive information retrieval (IR) contextually within a multitasking framework. The implications of our findings for Web design and further research are discussed.

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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

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

The dichotomous bipolar approach to relevance has produced an abundance of information retrieval (M) research. However, relevance studies that include consideration of users' partial relevance judgments are moving to a greater relevance clarity and congruity to impact the design of more effective [R systems. The study reported in this paper investigates the various regions of across a distribution of users' relevance judgments, including how these regions may be categorized, measured, and evaluated. An instrument was designed using four scales for collecting, measuring, and describing enduser relevance judgments. The instrument was administered to 21 end-users who conducted searches on their own information problems and made relevance judgments on a total of 1059 retrieved items. Findings include: (1) overlapping regions of relevance were found to impact the usefulness of precision ratios as a measure of IR system effectiveness, (2) both positive and negative levels of relevance are important to users as they make relevance judgments, (3) topicality was used more to reject rather than accept items as highly relevant, (4) utility was more used to judge items highly relevant, and (5) the nature of relevance judgment distribution suggested a new IR evaluation measure-median effect. Findings suggest that the middle region of a distribution of relevance judgments, also called "partial relevance," represents a key avenue for ongoing study. The findings provide implications for relevance theory, and the evaluation of IR systems

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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.