Information retrieval on the web

Kobayashi, Mei; Takeda, Koichi

doi:10.1145/358923.358934

Cited by 430 publications

(228 citation statements)

References 119 publications

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“…While it would be possible to measure the precision over larger sets of documents, the opportunity for improvements diminishes as we approach the size of search results set used in this evaluation. Note that while it is common in information retrieval research to also use the recall metric (ratio of relevant documents retrieved to the total relevant documents in the collection), the calculation of this metric with respect to Web search is not feasible due to the immense size of the collection (billions of documents) [9].…”

Section: "Journalist Risks"mentioning

confidence: 99%

Automatic Topic Learning for Personalized Re-Ordering of Web Search Results

Hoeber

Massie

2010

Advances in Soft Computing

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The fundamental idea behind personalization is to first learn something about the users of a system, and then use this information to support their future activities. When effective algorithms can be developed to learn user preferences, and when the methods for supporting future actions are achievable, personalization can be very effective. However, personalization is difficult in domains where tracking users, learning their preferences, and affecting their future actions is not obvious. In this paper, we introduce a novel method for providing personalized re-ordering of Web search results, based on allowing the searcher to maintain distinct search topics. Search results viewed during the search process are monitored, allowing the system to automatically learn about the users' current interests. The results of an evaluation study show improvements in the precision of the top 10 and 20 documents in the personalized search results after selecting as few as two relevant documents.

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Section: "Journalist Risks"mentioning

confidence: 99%

Automatic Topic Learning for Personalized Re-Ordering of Web Search Results

Hoeber

Massie

2010

Advances in Soft Computing

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“…Users can typically not directly influence search results, even if there are only few or bad results. While the early days of the Web favoured human-maintained "catalogues" which did not scale up [KT00], automated indexing and retrieval approaches largely keep human users out of the loop and can thus become increasingly cluttered and irrelevant-i.e. do not scale down well.…”

Section: Enterprise Searchmentioning

confidence: 99%

Professional Knowledge Management

Althoff¹,

Dengel²,

Bergmann³

et al. 2005

Lecture Notes in Computer Science

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publishes this series in order to make available to a broad public recent findings in informatics (i.e. computer science and information systems), to document conferences that are organized in cooperation with GI and to publish the annual GI Award dissertation.Broken down into the fields of • Seminar • Proceedings • Dissertations • Thematics current topics are dealt with from the fields of research and development, teaching and further training in theory and practice. The Editorial Committee uses an intensive review process in order to ensure the high level of the contributions.The volumes are published in German or English.Information: http://www.gi-ev.de/service/publikationen/lni/ The WM2009 is the 5th conference of the bi-annual series "Professional Knowledge Management". A broad integrative overview on currents trends and new insights in organisational, social and technical aspects of knowledge management are provided to participants from academia and practice. The conference programme is composed of 11 Workshops, invited talks, tutorials, a poster and demo session and an exhibition. It also provides space to discuss problems and challenges, share experiences and for networking. This volume contains refereed contributions from the workshops. 145ISSN 1617-5468 ISBN 978-3-88579-239-0 PrefaceKnowledge has become more and more an imperative key success factor for each company. It plays a key role in many business processes, in product development and advanced customer satisfaction. This is particularly important as products are becoming more complex and processesm ore knowledge-intensive. Many companies are going to realize their knowledge potential and improve their knowledge management. New technologies like those known under the "Web2.0" label and new methods like intellectual capital statements support the improvement of knowledge management.The 5 th conference on Professional Knowledge Management provides a broad integrative overview of organizational,c ultural, social and technical aspects on knowledge management. Focus of the conference is bringing together different research disciplines and sharing experiences gained in the different areas where knowledge management is being applied. In particular the 5 th conference on Professional Knowledge Management consists of five tutorials and eleven workshops focusingo n current trends. Topics of these tutorials andworkshops include knowledge services and mashups, knowledge and social networks, convergence of knowledge management and e-learning, productive knowledge work, personal knowledge management, experience management, measuring and benchmarking the economical success of knowledge management, integrating knowledge base systems as well as knowledge management approaches specialised for SME, for companies from the financial sector, or for combination with enterprise communication.Ninety-five contributions were submitted to the workshops of which 45 were accepted as long papers and 20 as short paper. These 65 contributions are collected in this proceedin...

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“…Which means that, there is a need for a mechanism to retrieve such information [2] from hidden web for the user? The entry point to such hidden webs is through the forms [3,4].…”

Section: Introductionmentioning

confidence: 99%

Fetching the hidden information of web through specific Domains

Gupta¹

2014

IOSRJCE

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Information retrieval on the web

Cited by 430 publications

References 119 publications

Automatic Topic Learning for Personalized Re-Ordering of Web Search Results

Automatic Topic Learning for Personalized Re-Ordering of Web Search Results

Professional Knowledge Management

Fetching the hidden information of web through specific Domains

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