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 Liyun Ru

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Average citations per article4.52
Citation Count140
Publication count31
Publication years2006-2014
Available for download20
Average downloads per article379.20
Downloads (cumulative)7,584
Downloads (12 Months)318
Downloads (6 Weeks)69
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31 results found Export Results: bibtexendnoteacmrefcsv

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1
November 2014 Expert Systems with Applications: An International Journal: Volume 41 Issue 16, November, 2014
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 3

With the development of social networks, more and more users have a great need to search for people to follow (SPTF) to receive their tweets. According to our experiments, approximately 50% of social networks' lost users leave due to a lack of people to follow. In this paper, we define ...
Keywords: SPTF, Tag expansion and prediction, Ranking algorithm, Social network mining

2 published by ACM
February 2014 WSDM '14: Proceedings of the 7th ACM international conference on Web search and data mining
Publisher: ACM
Bibliometrics:
Citation Count: 4
Downloads (6 Weeks): 4,   Downloads (12 Months): 30,   Downloads (Overall): 357

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Using search engines to retrieve information has become an important part of people's daily lives. For most search engines, click information is an important factor in document ranking. As a result, some websites cheat to obtain a higher rank by fraudulently increasing clicks to their pages, which is referred to ...
Keywords: click spam, frequent sequential patterns, user session model, label propagation

3
December 2012 Decision Support Systems: Volume 54 Issue 1, December, 2012
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 0

Page quality estimation is one of the greatest challenges for Web search engines. Hyperlink analysis algorithms such as PageRank and TrustRank are usually adopted for this task. However, low quality, unreliable and even spam data in the Web hyperlink graph makes it increasingly difficult to estimate page quality effectively. Analyzing ...
Keywords: Web graph, Hyperlink analysis, PageRank, Quality estimation, User behavior analysis

4 published by ACM
August 2012 SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 3,   Downloads (12 Months): 20,   Downloads (Overall): 365

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Combating Web spam is one of the greatest challenges for Web search engines. State-of-the-art anti-spam techniques focus mainly on detecting varieties of spam strategies, such as content spamming and link-based spamming. Although these anti-spam approaches have had much success, they encounter problems when fighting against a continuous barrage of new ...
Keywords: spam detection, web search engine, semi-supervised algorithm, click-through data/bipartite graph, label propagation

5 published by ACM
March 2012 ACM Transactions on the Web (TWEB): Volume 6 Issue 1, March 2012
Publisher: ACM
Bibliometrics:
Citation Count: 6
Downloads (6 Weeks): 1,   Downloads (12 Months): 14,   Downloads (Overall): 766

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Combating Web spam has become one of the top challenges for Web search engines. State-of-the-art spam-detection techniques are usually designed for specific, known types of Web spam and are incapable of dealing with newly appearing spam types efficiently. With user-behavior analyses from Web access logs, a spam page-detection algorithm is ...
Keywords: user behavior analysis, Spam detection, Web search engine

6 published by ACM
February 2012 WSDM '12: Proceedings of the fifth ACM international conference on Web search and data mining
Publisher: ACM
Bibliometrics:
Citation Count: 5
Downloads (6 Weeks): 2,   Downloads (12 Months): 13,   Downloads (Overall): 272

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Click-through behaviors are treated as invaluable sources of user feedback and they have been leveraged in several commercial search engines in recent years. However, estimating unbiased relevance is always a challenging task because of position bias. To solve this problem, many researchers have proposed a variety of assumptions to model ...
Keywords: document relevance, click-through behavior, revisit, temporal hidden click model

7 published by ACM
December 2011 ACM Transactions on Asian Language Information Processing (TALIP): Volume 10 Issue 4, December 2011
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 3,   Downloads (12 Months): 13,   Downloads (Overall): 330

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Nowadays, user behavior analysis and collaborative filtering have drawn a large body of research in the machine learning community. The goal is either to enhance the user experience or discover useful information hidden in the data. In this article, we conduct extensive experiments on a Chinese input method data set, ...
Keywords: user behaviors, Related words retrieval, collaborative filtering, natural language processing, new word detection

8
August 2011 WI-IAT '11: Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 0,   Downloads (12 Months): 4,   Downloads (Overall): 46

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User behavior analysis has played an important role in Web information retrieval. Rare queries, whose frequencies are rather low, are usually ignored in existing studies due to the data sparseness. Little has been known about the mass of rare queries on either the information need or the user behavior. In ...

9
July 2011 IJCAI'11: Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Publisher: AAAI Press
Bibliometrics:
Citation Count: 3

The possibility that influenza activity can be generally detected through search log analysis has been explored in recent years. However, previous studies have mainly focused on influenza, and little attention has been paid to other epidemics. With an analysis of web user behavior data, we consider the problem of predicting ...

10
June 2011 HLT '11: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Publisher: Association for Computational Linguistics
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 1,   Downloads (12 Months): 10,   Downloads (Overall): 166

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Chinese Pinyin input method is very important for Chinese language information processing. Users may make errors when they are typing in Chinese words. In this paper, we are concerned with the reasons that cause the errors. Inspired by the observation that pressing backspace is one of the most common user ...

11
May 2011 PAKDD'11: Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

Sponsored advertisement(ad) has already become the major source of revenue for most popular search engines. One fundamental challenge facing all search engines is how to achieve a balance between the number of displayed ads and the potential annoyance to the users. Displaying more ads would improve the chance for the ...

12 published by ACM
March 2011 WWW '11: Proceedings of the 20th international conference companion on World wide web
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 6,   Downloads (Overall): 103

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Ground truth labels are one of the most important parts in many test collections for information retrieval. Each label, depicting the relevance between a query-document pair, is usually judged by a human, and this process is time-consuming and labor-intensive. Automatically Generating labels from click-through data has attracted increasing attention. In ...
Keywords: click model, learning to rank, ranking SVM

13 published by ACM
April 2010 WWW '10: Proceedings of the 19th international conference on World wide web
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 5,   Downloads (12 Months): 14,   Downloads (Overall): 252

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In this paper, we study on the reliability of search engine users using click-through data. We proposed a graph-based approach to evaluate user reliability according to how users click on search result lists. We tried to incorporate this measure of reliability into relevance feedback for improving ranking performances. Experimental results ...
Keywords: relevance feedback, user reliability, web search

14 published by ACM
April 2010 WWW '10: Proceedings of the 19th international conference on World wide web
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 12,   Downloads (Overall): 257

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Under different language contexts, people choose different terms or phrases to express their feelings and opinions. When a user is writing a paper or chatting with a friend, he/she applies a specific language model corresponding to the underlying goal. This paper presents a log-based study of analyzing the language models ...
Keywords: language model, log analysis, user goal

15 published by ACM
April 2010 WWW '10: Proceedings of the 19th international conference on World wide web
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 4,   Downloads (12 Months): 17,   Downloads (Overall): 334

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We consider the problem of detecting epidemic tendency by mining search logs. We propose an algorithm based on click-through information to select epidemic related queries/terms. We adopt linear regression to model epidemic occurrences and frequencies of epidemic related terms (ERTs) in search logs. The results show our algorithm is effective ...
Keywords: epidemic detection, search log mining, query

16 published by ACM
April 2010 WWW '10: Proceedings of the 19th international conference on World wide web
Publisher: ACM
Bibliometrics:
Citation Count: 4
Downloads (6 Weeks): 3,   Downloads (12 Months): 14,   Downloads (Overall): 424

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Ranking is an essential part of information retrieval(IR) tasks such as Web search. Nowadays there are hundreds of features for ranking. So learning to rank(LTR), an interdisciplinary field of IR and machine learning(ML), has attracted increasing attention. Those features used in the IR are not always independent from each other, ...
Keywords: feature selection, learning to rank

17 published by ACM
November 2009 CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 10,   Downloads (Overall): 311

Full text available: PDFPDF
Mining feedback information from user click-through data is an important issue for modern Web retrieval systems in terms of architecture analysis, performance evaluation and algorithm optimization. For commercial search engines, user click-through data contains useful information as well as large amount of inevitable noises. This paper proposes an approach to ...
Keywords: click relevance, click-through data, implicit feedback, long-tail query

18
October 2009 AIRS '09: Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

Relevance evaluation is an important topic in Web search engine research. Traditional evaluation methods resort to huge amount of human efforts which lead to an extremely time-consuming process in practice. With analysis on large scale user query logs and click-through data, we propose a performance evaluation method that fully automatically ...
Keywords: Performance evaluation, click-through data analysis, Web search engine, the wisdom of crowds

19
October 2009 AIRS '09: Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 4

Combating Web spam has become one of the top challenges for Web search engines. Most previous researches in link-based Web spam identification focus on exploiting hyperlink graphs and corresponding user-behavior models. However, the fact that hyperlinks can be easily added and removed by Web spammers makes hyperlink graph unreliable. We ...
Keywords: Spam identification, TrustRank, User browsing graph

20
October 2009 AIRS '09: Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 1

User behavior information analysis has been shown important for optimization and evaluation of Web search and has become one of the major areas in both information retrieval and knowledge management researches. This paper focuses on users' searching behavior reliability study based on large scale query and click-through logs collected from ...
Keywords: User behavior analysis, click reliability, search user, search engine



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