Search (8 results, page 1 of 1)

  • × theme_ss:"Retrievalalgorithmen"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × year_i:[1990 TO 2000}
  1. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.03 
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    Abstract
    Keyword based querying has been an immediate and efficient way to specify and retrieve related information that the user inquired. However, conventional document ranking based on an automatic assessment of document relevance to the query may not be the best approach when little information is given. Proposes an idea to integrate 2 existing techniques, query expansion and relevance feedback to achieve a concept-based information search for the Web
    Date
    1. 8.1996 22:08:06
    Footnote
    Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia
    Type
    a
  2. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.02 
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    Abstract
    The performance of 8 ranking algorithms was evaluated with respect to their effectiveness in ranking terms for query expansion. The evaluation was conducted within an investigation of interactive query expansion and relevance feedback in a real operational environment. Focuses on the identification of algorithms that most effectively take cognizance of user preferences. user choices (i.e. the terms selected by the searchers for the query expansion search) provided the yardstick for the evaluation of the 8 ranking algorithms. This methodology introduces a user oriented approach in evaluating ranking algorithms for query expansion in contrast to the standard, system oriented approaches. Similarities in the performance of the 8 algorithms and the ways these algorithms rank terms were the main focus of this evaluation. The findings demonstrate that the r-lohi, wpq, enim, and porter algorithms have similar performance in bringing good terms to the top of a ranked list of terms for query expansion. However, further evaluation of the algorithms in different (e.g. full text) environments is needed before these results can be generalized beyond the context of the present study
    Date
    22. 2.1996 13:14:10
    Source
    Information processing and management. 31(1995) no.4, S.605-620
    Type
    a
  3. Kwok, K.L.: ¬A network approach to probabilistic information retrieval (1995) 0.01 
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    Abstract
    Shows how probabilistic information retrieval based on document components may be implemented as a feedforward (feedbackward) artificial neural network. The network supports adaptation of connection weights as well as the growing of new edges between queries and terms based on user relevance feedback data for training, and it reflects query modification and expansion in information retrieval. A learning rule is applied that can also be viewed as supporting sequential learning using a harmonic sequence learning rate. Experimental results with 4 standard small collections and a large Wall Street Journal collection show that small query expansion levels of about 30 terms can achieve most of the gains at the low-recall high-precision region, while larger expansion levels continue to provide gains at the high-recall low-precision region of a precision recall curve
    Source
    ACM transactions on information systems. 13(1995) no.3, S.324-353
    Type
    a
  4. Beaulieu, M.; Jones, S.: Interactive searching and interface issues in the Okapi best match probabilistic retrieval system (1998) 0.01 
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    Abstract
    Explores interface design raised by the development and evaluation of Okapi, a highly interactive information retrieval system based on a probabilistic retrieval model with relevance feedback. It uses terms frequency weighting functions to display retrieved items in a best match ranked order; it can also find additional items similar to those marked as relevant by the searcher. Compares the effectiveness of automatic and interactive query expansion in different user interface environments. focuses on the nature of interaction in information retrieval and the interrelationship between functional visibility, the user's cognitive loading and the balance of control between user and system
    Type
    a
  5. Srinivasan, P.: Query expansion and MEDLINE (1996) 0.01 
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    Abstract
    Evaluates the retrieval effectiveness of query expansion strategies on a test collection of the medical database MEDLINE using Cornell University's SMART retrieval system. Tests 3 expansion strategies for their ability to identify appropriate MeSH terms for user queries. Compares retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a collection of 75 queries and 2.334 Medline citations. Recommends query expansions using retrieval feedback for adding MeSH search terms to a user's initial query
    Source
    Information processing and management. 32(1996) no.4, S.431-443
    Type
    a
  6. Chen, H.; Zhang, Y.; Houston, A.L.: Semantic indexing and searching using a Hopfield net (1998) 0.01 
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    Abstract
    Presents a neural network approach to document semantic indexing. Reports results of a study to apply a Hopfield net algorithm to simulate human associative memory for concept exploration in the domain of computer science and engineering. The INSPEC database, consisting of 320.000 abstracts from leading periodical articles was used as the document test bed. Benchmark tests conformed that 3 parameters: maximum number of activated nodes; maximum allowable error; and maximum number of iterations; were useful in positively influencing network convergence behaviour without negatively impacting central processing unit performance. Another series of benchmark tests was performed to determine the effectiveness of various filtering techniques in reducing the negative impact of noisy input terms. Preliminary user tests conformed expectations that the Hopfield net is potentially useful as an associative memory technique to improve document recall and precision by solving discrepancies between indexer vocabularies and end user vocabularies
    Source
    Journal of information science. 24(1998) no.1, S.3-18
    Type
    a
  7. Robertson, S.E.: OKAPI at TREC-3 (1995) 0.00 
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    Abstract
    Reports text information retrieval experiments performed as part of the 3 rd round of Text Retrieval Conferences (TREC) using the Okapi online catalogue system at City University, UK. The emphasis in TREC-3 was: further refinement of term weighting functions; an investigation of run time passage determination and searching; expansion of ad hoc queries by terms extracted from the top documents retrieved by a trial search; new methods for choosing query expansion terms after relevance feedback, now split into methods of ranking terms prior to selection and subsequent selection procedures; and the development of a user interface procedure within the new TREC interactive search framework
  8. Hancock-Beaulieu, M.; Walker, S.: ¬An evaluation of automatic query expansion in an online library catalogue (1992) 0.00 
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    Abstract
    An automatic query expansion (AQE) facility in anonline catalogue was evaluated in an operational library setting. The OKAPI experimental system had other features including: ranked output 'best match' keyword searching, automatic stemming, spelling normalisation and cross referencing as well as relevance feedback. A combination of transaction log analysis, search replays, questionnaires and interviews was used for data collection. Findings show that contrary to previous results, AQE was beneficial in a substantial number of searches. Use intentions, the effectiveness of the 'best match' search and user interaction were identified as the main factors affecting the take-up of the query expansion facility
    Type
    a

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