Search (29 results, page 1 of 2)

  • × theme_ss:"Suchtaktik"
  1. Wang, P.; Berry, M.W.; Yang, Y.: Mining longitudinal Web queries : trends and patterns (2003) 0.04
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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.
  2. Kang, X.; Wu, Y.; Ren, W.: Toward action comprehension for searching : mining actionable intents in query entities (2020) 0.04
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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.
  3. Morse, P.M.: Search theory and browsing (1970) 0.03
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    Date
    22. 5.2005 19:53:09
  4. Morse, P.M.: Browsing and search theory (1973) 0.02
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    Date
    22. 5.2005 19:52:29
  5. Branch, J.L.: Investigating the information-seeking process of adolescents : the value of using think alouds and think afters (2000) 0.02
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    Source
    Library and information science research. 22(2000) no.4, S.371-382
  6. Barrio, P.; Gravano, L.: Sampling strategies for information extraction over the deep web (2017) 0.02
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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.
  7. Pejtersen, A.M.: Design of a classification scheme for fiction based on an analysis of actual user-librarian communication, and use of the scheme for control of librarians' search strategies (1980) 0.02
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    Date
    5. 8.2006 13:22:44
  8. Hsieh-Yee, I.: Search tactics of Web users in searching for texts, graphics, known items and subjects : a search simulation study (1998) 0.01
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    Date
    25.12.1998 19:22:31
  9. Limberg, L.: Three conceptions of information seeking and use (1999) 0.01
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    Date
    22. 3.2002 9:53:10
  10. Lin, S.-j.; Belkin, N.: Validation of a model of information seeking over multiple search sessions (2005) 0.01
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    Date
    10. 4.2005 14:52:22
  11. Koopmans, N.I.: What's your question? : The need for research information from the perspective of different user groups (2002) 0.01
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    Date
    2. 7.2005 12:22:50
  12. Crestani, F.; Du, H.: Written versus spoken queries : a qualitative and quantitative comparative analysis (2006) 0.01
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    Date
    5. 6.2006 11:22:23
  13. Xu, Y.: ¬The dynamics of interactive information retrieval behavior : part I: an activity theory perspective (2007) 0.01
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    Date
    27. 5.2007 13:55:22
  14. Lee, S.-S.; Theng, Y.-L.; Goh, D.H.-L.: Creative information seeking : part II: empirical verification (2007) 0.01
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    Date
    23.12.2007 12:22:16
  15. Saastamoinen, M.; Järvelin, K.: Search task features in work tasks of varying types and complexity (2017) 0.01
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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.
  16. Byström, K.: Information seekers in context : an analysis of the 'doer' in INSU studies (1999) 0.01
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    Date
    22. 3.2002 9:55:52
  17. Vakkari, P.; Pennanen, M.; Serola, S.: Changes of search terms and tactics while writing a research proposal : a longitudinal case study (2003) 0.01
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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.
  18. Mansourian, Y.: Contextual elements and conceptual components of information visibility on the web (2008) 0.01
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    Date
    1. 1.2009 10:22:40
  19. Aloteibi, S.; Sanderson, M.: Analyzing geographic query reformulation : an exploratory study (2014) 0.01
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    Date
    26. 1.2014 18:48:22
  20. Monchaux, S.; Amadieu, F.; Chevalier, A.; Mariné, C.: Query strategies during information searching : effects of prior domain knowledge and complexity of the information problems to be solved (2015) 0.01
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    Date
    25. 1.2016 18:46:22