Search (18 results, page 1 of 1)

  • × theme_ss:"Retrievalalgorithmen"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Quiroga, L.M.; Mostafa, J.: ¬An experiment in building profiles in information filtering : the role of context of user relevance feedback (2002) 0.01 
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    Abstract
    An experiment was conducted to see how relevance feedback could be used to build and adjust profiles to improve the performance of filtering systems. Data was collected during the system interaction of 18 graduate students with SIFTER (Smart Information Filtering Technology for Electronic Resources), a filtering system that ranks incoming information based on users' profiles. The data set came from a collection of 6000 records concerning consumer health. In the first phase of the study, three different modes of profile acquisition were compared. The explicit mode allowed users to directly specify the profile; the implicit mode utilized relevance feedback to create and refine the profile; and the combined mode allowed users to initialize the profile and to continuously refine it using relevance feedback. Filtering performance, measured in terms of Normalized Precision, showed that the three approaches were significantly different ( [small alpha, Greek] =0.05 and p =0.012). The explicit mode of profile acquisition consistently produced superior results. Exclusive reliance on relevance feedback in the implicit mode resulted in inferior performance. The low performance obtained by the implicit acquisition mode motivated the second phase of the study, which aimed to clarify the role of context in relevance feedback judgments. An inductive content analysis of thinking aloud protocols showed dimensions that were highly situational, establishing the importance context plays in feedback relevance assessments. Results suggest the need for better representation of documents, profiles, and relevance feedback mechanisms that incorporate dimensions identified in this research.
    Source
    Information processing and management. 38(2002) no.5, S.671-694
  2. Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.01 
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    Abstract
    The study reported here investigated the query expansion behavior of end-users interacting with a thesaurus-enhanced search system on the Web. Two groups, namely academic staff and postgraduate students, were recruited into this study. Data were collected from 90 searches performed by 30 users using the OVID interface to the CAB abstracts database. Data-gathering techniques included questionnaires, screen capturing software, and interviews. The results presented here relate to issues of search-topic and search-term characteristics, number and types of expanded queries, usefulness of thesaurus terms, and behavioral differences between academic staff and postgraduate students in their interaction. The key conclusions drawn were that (a) academic staff chose more narrow and synonymous terms than did postgraduate students, who generally selected broader and related terms; (b) topic complexity affected users' interaction with the thesaurus in that complex topics required more query expansion and search term selection; (c) users' prior topic-search experience appeared to have a significant effect on their selection and evaluation of thesaurus terms; (d) in 50% of the searches where additional terms were suggested from the thesaurus, users stated that they had not been aware of the terms at the beginning of the search; this observation was particularly noticeable in the case of postgraduate students.
    Date
    22. 7.2006 16:32:43
  3. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.01 
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    Abstract
    The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.
    Date
    16.11.2008 16:22:48
  4. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.01 
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    Date
    22. 2.1996 13:14:10
    Source
    Information processing and management. 31(1995) no.4, S.605-620
  5. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.00 
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    Date
    30. 3.2001 13:32:22
  6. 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
  7. Srinivasan, P.: Query expansion and MEDLINE (1996) 0.00 
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    Source
    Information processing and management. 32(1996) no.4, S.431-443
  8. Kwok, K.L.: ¬A network approach to probabilistic information retrieval (1995) 0.00 
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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
  9. Bhogal, J.; Macfarlane, A.; Smith, P.: ¬A review of ontology based query expansion (2007) 0.00 
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    Source
    Information processing and management. 43(2007) no.4, S.866-886
  10. Efthimiadis, E.N.: Interactive query expansion : a user-based evaluation in a relevance feedback environment (2000) 0.00 
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    Abstract
    A user-centered investigation of interactive query expansion within the context of a relevance feedback system is presented in this article. Data were collected from 25 searches using the INSPEC database. The data collection mechanisms included questionnaires, transaction logs, and relevance evaluations. The results discuss issues that relate to query expansion, retrieval effectiveness, the correspondence of the on-line-to-off-line relevance judgments, and the selection of terms for query expansion by users (interactive query expansion). The main conclusions drawn from the results of the study are that: (1) one-third of the terms presented to users in a list of candidate terms for query expansion was identified by the users as potentially useful for query expansion. (2) These terms were mainly judged as either variant expressions (synonyms) or alternative (related) terms to the initial query terms. However, a substantial portion of the selected terms were identified as representing new ideas. (3) The relationships identified between the five best terms selected by the users for query expansion and the initial query terms were that: (a) 34% of the query expansion terms have no relationship or other type of correspondence with a query term; (b) 66% of the remaining query expansion terms have a relationship to the query terms. These relationships were: narrower term (46%), broader term (3%), related term (17%). (4) The results provide evidence for the effectiveness of interactive query expansion. The initial search produced on average three highly relevant documents; the query expansion search produced on average nine further highly relevant documents. The conclusions highlight the need for more research on: interactive query expansion, the comparative evaluation of automatic vs. interactive query expansion, the study of weighted Webbased or Web-accessible retrieval systems in operational environments, and for user studies in searching ranked retrieval systems in general
  11. Symonds, M.; Bruza, P.; Zuccon, G.; Koopman, B.; Sitbon, L.; Turner, I.: Automatic query expansion : a structural linguistic perspective (2014) 0.00 
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    Abstract
    A user's query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques model syntagmatic associations that infer two terms co-occur more often than by chance in natural language. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches to query expansion and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process improves retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.
  12. Bhansali, D.; Desai, H.; Deulkar, K.: ¬A study of different ranking approaches for semantic search (2015) 0.00 
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    Abstract
    Search Engines have become an integral part of our day to day life. Our reliance on search engines increases with every passing day. With the amount of data available on Internet increasing exponentially, it becomes important to develop new methods and tools that help to return results relevant to the queries and reduce the time spent on searching. The results should be diverse but at the same time should return results focused on the queries asked. Relation Based Page Rank [4] algorithms are considered to be the next frontier in improvement of Semantic Web Search. The probability of finding relevance in the search results as posited by the user while entering the query is used to measure the relevance. However, its application is limited by the complexity of determining relation between the terms and assigning explicit meaning to each term. Trust Rank is one of the most widely used ranking algorithms for semantic web search. Few other ranking algorithms like HITS algorithm, PageRank algorithm are also used for Semantic Web Searching. In this paper, we will provide a comparison of few ranking approaches.
  13. Chen, H.; Zhang, Y.; Houston, A.L.: Semantic indexing and searching using a Hopfield net (1998) 0.00 
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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
  14. Zhang, W.; Yoshida, T.; Tang, X.: ¬A comparative study of TF*IDF, LSI and multi-words for text classification (2011) 0.00 
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    Abstract
    One of the main themes in text mining is text representation, which is fundamental and indispensable for text-based intellegent information processing. Generally, text representation inludes two tasks: indexing and weighting. This paper has comparatively studied TF*IDF, LSI and multi-word for text representation. We used a Chinese and an English document collection to respectively evaluate the three methods in information retreival and text categorization. Experimental results have demonstrated that in text categorization, LSI has better performance than other methods in both document collections. Also, LSI has produced the best performance in retrieving English documents. This outcome has shown that LSI has both favorable semantic and statistical quality and is different with the claim that LSI can not produce discriminative power for indexing.
  15. Jindal, V.; Bawa, S.; Batra, S.: ¬A review of ranking approaches for semantic search on Web (2014) 0.00 
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    Source
    Information processing and management. 50(2014) no.2, S.416-425
  16. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.00 
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    Date
    1. 8.1996 22:08:06
  17. Liu, X.; Zheng, W.; Fang, H.: ¬An exploration of ranking models and feedback method for related entity finding (2013) 0.00 
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    Source
    Information processing and management. 49(2013) no.5, S.995-1007
  18. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.00 
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    Date
    22. 3.2003 19:35:46

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