Search (294 results, page 15 of 15)

MacFarlane, A.; McCann, J.A.; Robertson, S.E.: Parallel methods for the update of partitioned inverted files (2007) 0.00
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Abstract

Purpose - An issue that tends to be ignored in information retrieval is the issue of updating inverted files. This is largely because inverted files were devised to provide fast query service, and much work has been done with the emphasis strongly on queries. This paper aims to study the effect of using parallel methods for the update of inverted files in order to reduce costs, by looking at two types of partitioning for inverted files: document identifier and term identifier. Design/methodology/approach - Raw update service and update with query service are studied with these partitioning schemes using an incremental update strategy. The paper uses standard measures used in parallel computing such as speedup to examine the computing results and also the costs of reorganising indexes while servicing transactions. Findings - Empirical results show that for both transaction processing and index reorganisation the document identifier method is superior. However, there is evidence that the term identifier partitioning method could be useful in a concurrent transaction processing context. Practical implications - There is an increasing need to service updates, which is now becoming a requirement of inverted files (for dynamic collections such as the web), demonstrating that a shift in requirements of inverted file maintenance is needed from the past. Originality/value - The paper is of value to database administrators who manage large-scale and dynamic text collections, and who need to use parallel computing to implement their text retrieval services.

Ning, X.; Jin, H.; Wu, H.: RSS: a framework enabling ranked search on the semantic web (2008) 0.00

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Source: Information processing and management. 44(2008) no.2, S.893-909

Li, X.: ¬A new robust relevance model in the language model framework (2008) 0.00

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Source: Information processing and management. 44(2008) no.3, S.991-1007

Wan, X.; Yang, J.; Xiao, J.: Towards a unified approach to document similarity search using manifold-ranking of blocks (2008) 0.00

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Source: Information processing and management. 44(2008) no.3, S.1032-1048

Wei, F.; Li, W.; Liu, S.: iRANK: a rank-learn-combine framework for unsupervised ensemble ranking (2010) 0.00

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Source: Journal of the American Society for Information Science and Technology. 61(2010) no.6, S.1232-1243

Schaefer, A.; Jordan, M.; Klas, C.-P.; Fuhr, N.: Active support for query formulation in virtual digital libraries : a case study with DAFFODIL (2005) 0.00
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Abstract

Daffodil is a front-end to federated, heterogeneous digital libraries targeting at strategic support of users during the information seeking process. This is done by offering a variety of functions for searching, exploring and managing digital library objects. However, the distributed search increases response time and the conceptual model of the underlying search processes is inherently weaker. This makes query formulation harder and the resulting waiting times can be frustrating. In this paper, we investigate the concept of proactive support during the user's query formulation. For improving user efficiency and satisfaction, we implemented annotations, proactive support and error markers on the query form itself. These functions decrease the probability for syntactical or semantical errors in queries. Furthermore, the user is able to make better tactical decisions and feels more confident that the system handles the query properly. Evaluations with 30 subjects showed that user satisfaction is improved, whereas no conclusive results were received for efficiency.

He, J.; Meij, E.; Rijke, M. de: Result diversification based on query-specific cluster ranking (2011) 0.00

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Source: Journal of the American Society for Information Science and Technology. 62(2011) no.3, S.550-571

Silva, R.M.; Gonçalves, M.A.; Veloso, A.: ¬A Two-stage active learning method for learning to rank (2014) 0.00

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Source: Journal of the Association for Information Science and Technology. 65(2014) no.1, S.109-128

Tsai, C.-F.; Hu, Y.-H.; Chen, Z.-Y.: Factors affecting rocchio-based pseudorelevance feedback in image retrieval (2015) 0.00

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Source: Journal of the Association for Information Science and Technology. 66(2015) no.1, S.40-57

Zhu, J.; Han, L.; Gou, Z.; Yuan, X.: ¬A fuzzy clustering-based denoising model for evaluating uncertainty in collaborative filtering recommender systems (2018) 0.00

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Source: Journal of the Association for Information Science and Technology. 69(2018) no.9, S.1109-1121

Jiang, J.-D.; Jiang, J.-Y.; Cheng, P.-J.: Cocluster hypothesis and ranking consistency for relevance ranking in web search (2019) 0.00

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Source: Journal of the Association for Information Science and Technology. 70(2019) no.6, S.535-546

Purpura, A.; Silvello, G.; Susto, G.A.: Learning to rank from relevance judgments distributions (2022) 0.00

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Source: Journal of the Association for Information Science and Technology. 73(2022) no.9, S.1236-1252

Efthimiadis, E.N.: Interactive query expansion : a user-based evaluation in a relevance feedback environment (2000) 0.00

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Source: Journal of the American Society for Information Science. 51(2000) no.11, S.989-1003

Bar-Ilan, J.; Levene, M.; Mat-Hassan, M.: Methods for evaluating dynamic changes in search engine rankings : a case study (2006) 0.00
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Abstract

Purpose - The objective of this paper is to characterize the changes in the rankings of the top ten results of major search engines over time and to compare the rankings between these engines. Design/methodology/approach - The papers compare rankings of the top-ten results of the search engines Google and AlltheWeb on ten identical queries over a period of three weeks. Only the top-ten results were considered, since users do not normally inspect more than the first results page returned by a search engine. The experiment was repeated twice, in October 2003 and in January 2004, in order to assess changes to the top-ten results of some of the queries during the three months interval. In order to assess the changes in the rankings, three measures were computed for each data collection point and each search engine. Findings - The findings in this paper show that the rankings of AlltheWeb were highly stable over each period, while the rankings of Google underwent constant yet minor changes, with occasional major ones. Changes over time can be explained by the dynamic nature of the web or by fluctuations in the search engines' indexes. The top-ten results of the two search engines had surprisingly low overlap. With such small overlap, the task of comparing the rankings of the two engines becomes extremely challenging. Originality/value - The paper shows that because of the abundance of information on the web, ranking search results is of extreme importance. The paper compares several measures for computing the similarity between rankings of search tools, and shows that none of the measures is fully satisfactory as a standalone measure. It also demonstrates the apparent differences in the ranking algorithms of two widely used search engines.

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