Search (31 results, page 1 of 2)

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Abstract

In information needs, seeking and use (INSU) research, individuals have most commonly been perceived as users (e.g., Kuhlthau, 1991; Dervin & Nilan, 1986; Dervin, 1989; Belkin, 1980). The concept user originates from the user of libraries and other information services and information systems. Over the years the scope of the concept has become wider and it is nowadays often understood in the sense of seekers of information (e.g., Wilson, 1981; Marchionini, 1995) and users of information (e.g., Streatfield, 1983). Nevertheless, the concept has remained ambiguous by being on the one hand universal and on the other hand extremely specific. The purpose of this paper is to map and evaluate views on people whose information behaviour has been in one way or another the core of our research area. The goal is to shed some light on various relationships between the different aspects of doers in INSU studies. The paper is inspired by Dervin's (1997) analysis of context where she identified among other themes the nature of subject by contrasting a `transcendental individual' with a `decentered subject', and Talja's (1997) presentation about constituting `information' and `user' from the discourse analytic viewpoint as opposed to the cognitive viewpoint. Instead of the metatheoretical approach applied by Dervin and Talja, a more concrete approach is valid in the present analysis where no direct arguments for or against the underlying metatheories are itemised. The focus is on doers in INSU studies leaving other, even closely-related concepts (i.e., information, information seeking, knowledge etc.), outside the scope of the paper.

Date

22. 3.2002 9:55:52

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Abstract

This project analyzed 541,920 user queries submitted to and executed in an academic Website during a four-year period (May 1997 to May 2001) using a relational database. The purpose of the study is three-fold: (1) to understand Web users' query behavior; (2) to identify problems encountered by these Web users; (3) to develop appropriate techniques for optimization of query analysis and mining. The linguistic analyses focus an query structures, lexicon, and word associations using statistical measures such as Zipf distribution and mutual information. A data model with finest granularity is used for data storage and iterative analyses. Patterns and trends of querying behavior are identified and compared with previous studies.

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Abstract

Understanding search engine users' intents has been a popular study in information retrieval, which directly affects the quality of retrieved information. One of the fundamental problems in this field is to find a connection between the entity in a query and the potential intents of the users, the latter of which would further reveal important information for facilitating the users' future actions. In this article, we present a novel research method for mining the actionable intents for search users, by generating a ranked list of the potentially most informative actions based on a massive pool of action samples. We compare different search strategies and their combinations for retrieving the action pool and develop three criteria for measuring the informativeness of the selected action samples, that is, the significance of an action sample within the pool, the representativeness of an action sample for the other candidate samples, and the diverseness of an action sample with respect to the selected actions. Our experiment, based on the Action Mining (AM) query entity data set from the Actionable Knowledge Graph (AKG) task at NTCIR-13, suggests that the proposed approach is effective in generating an informative and early-satisfying ranking of potential actions for search users.

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Date

22. 5.2005 19:53:09

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Date

22. 5.2005 19:52:29

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Source

Library and information science research. 22(2000) no.4, S.371-382

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Abstract

Research in information science aims to comprehend the facilitation of access to information for supporting purposeful action. The major themes to be addressed have been how information is organized for access, how it is retrieved from storage, and how it is sought out and used for various purposes. Two central research areas in the field are information retrieval (IR) and information seeking (IS) (Vakkari & Rochester, 1998). Although intuitively the fields seem to be overlapping, their research communities have been active in their own enclosures. Few researchers have visited the neighboring side. However, there are researchers (Bates, 1989; Belkin & Vickery, 1986; Belkin, 1993; Ellis, 1989; Ingwersen, 1992, 1996; Järvelin 1987; Kuhlthau, 1993; Marchionini, 1995; Saracevic & Kantor, 1988) who have stressed the need to connect results from both research traditions. IR can be seen as a part of a broader process of information seeking. By IS is understood a process of searching, obtaining and using information for a purpose (e.g., form a solution for a task) when a person does not have sufficient prior knowledge. By 1R is understood the use of an information system for obtaining relevant information for a purpose (e.g., a task). This implies that information systems are a specific means among other sources and channels for obtaining information.

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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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Date

5. 8.2006 13:22:44

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Footnote

Rez. in: JASIST 54(2003) no.7, S.695-697 (R. Savolainen): "Donald O. Case has written an ambitious book to create an overall picture of the major approaches to information needs and seeking (INS) studies. The aim to write an extensive review is reflected in the list of references containing about 700 items. The high ambitions are explained an p. 14, where Case states that he is aiming at a multidisciplinary understanding of the concept of information seeking. In the Preface, the author characterizes his book as an introduction to the topic for students at the graduate level, as well as as a review and handbook for scholars engagged in information behavior research. In my view, Looking for Information is particularly welcome as an academic textbook because the field of INS studies suffers from the lack of monographs. Along with the continuous growth of the number of journal articles and conference papers, there is a genuine need for a book that picks up the numerous pieces and puts them together. The use of the study as a textbook is facilitated by clearly delineated sections an major themes and the wealth of concrete examples of information seeking in everyday contexts. The book is lucidly written and it is accessible to novice readers, too. At first glance, the idea of providing a comprehensive review of INS studies may seem a mission impossible because the current number of articles, papers, and other contributions in this field is nearing the 10,000 range (p. 224). Donald Case is not alone in the task of coming to grips with an increasing number of studies; similar problems have been faced by those writing INS-related chapters for the Annual Review of Information Science and Technology (ARIST). Case has solved the problem of "too many publications to be reviewed" by concentrating an the INS literature published during the last two decades. Secondly, studies an library use and information retrieval are discussed only to a limited extent. In addition, Case is highly selective as to studies focusing an the use of specific sources and channels such as WWW. These delineations are reasonable, even though they beg some questions. First, how should one draw the line between studies an information seeking and information retrieval? Case does not discuss this question in greater detail, although in recent years, the overlapping areas of information seeking and retrieval studies have been broadened, along with the growing importance of WWW in information seeking/retrieval. Secondly, how can one define the concept of information searching (or, more specifically, Internet or Web searching) in relation to information seeking and information retrieval? In the field of Web searching studies, there is an increasing number of contributions that are of direct relevance to information-seeking studies. Clearly, the advent of the Internet, particularly, the Web, has blurred the previous lines between INS and IR literature, making them less clear cut. The book consists of five main sections, and comprises 13 chapters. There is an Appendix serving the needs of an INS textbook (questions for discussion and application). The structure of the book is meticulously planned and, as a whole, it offers a sufficiently balanced contribution to theoretical, methodological, and empirical issues of INS. The title, Looking for Information: A Survey of Research an Information Seeking, Needs, and Behavior aptly describes the main substance of the book. . . . It is easy to agree with Case about the significance of the problem of specialization and fragmentation. This problem seems to be concomitant with the broadening field of INS research. In itself, Case's book can be interpreted as a struggle against this fragmentation. His book suggests that this struggle is not hopeless and that it is still possible to draw an overall picture of the evolving research field. The major pieces of the puzzle were found and the book will provide a useful overview of INS studies for many years."

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Date

25.12.1998 19:22:31

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Date

22. 3.2002 9:53:10

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Date

10. 4.2005 14:52:22

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Date

2. 7.2005 12:22:50

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Date

5. 6.2006 11:22:23

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Date

27. 5.2007 13:55:22

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Date

23.12.2007 12:22:16

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Abstract

Information searching in practice seldom is an end in itself. In work, work task (WT) performance forms the context, which information searching should serve. Therefore, information retrieval (IR) systems development/evaluation should take the WT context into account. The present paper analyzes how WT features: task complexity and task types, affect information searching in authentic work: the types of information needs, search processes, and search media. We collected data on 22 information professionals in authentic work situations in three organization types: city administration, universities, and companies. The data comprise 286 WTs and 420 search tasks (STs). The data include transaction logs, video recordings, daily questionnaires, interviews. and observation. The data were analyzed quantitatively. Even if the participants used a range of search media, most STs were simple throughout the data, and up to 42% of WTs did not include searching. WT's effects on STs are not straightforward: different WT types react differently to WT complexity. Due to the simplicity of authentic searching, the WT/ST types in interactive IR experiments should be reconsidered.

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Abstract

The study analyses how students' growing understanding of the topic and search experience were related to their choice of search tactics and terms while preparing a research proposal for a small empirical study. In addition to that, the findings of the study are used to test Vakkari's (2001) theory of task-based IR. The research subjects were 22 students of psychology attending a seminar for preparing the proposal. They made a search for their task in PsychINFO database at the beginning and end of the seminar. Data were collected in several ways. A pre- and post-search interview was conducted in both sessions. The students were asked to think aloud in the sessions. This was recorded as were the transaction logs. The results show that search experience was slightly related to the change of facets. Although the students' vocabulary of the topic grew generating an increased use of specific terms between the sessions, their use of search tactics and operators remained fairly constant. There was no correlation between the terms and tactics used and the total number of useful references found. By comparing these results with the findings of relevant earlier studies the conclusion was drawn that domain knowledge has an impact on searching assuming that users have a sufficient command of the system used. This implies that the tested theory of task-based IR is valid on condition that the searchers are experienced. It is suggested that the theory should be enriched by including search experience in its scope.

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Date

1. 1.2009 10:22:40