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37 Result(s)

within **li Meng Remove this filter Computer Science Remove this filter Data Mining and Knowledge Discovery Remove this filter Information Storage and Retrieval Remove this filter Information Systems and Communication Service Remove this filter

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  1. No Access

    Article

    Searching the Web with Queries

    In this paper we study the problem of searching the Web with online learning algorithms. We consider that Web documents can be represented by vectors of n boolean attributes. A search engine is viewed as a lea...

    Zhixiang Chen, **annong Meng, Richard H. Fowler in Knowledge and Information Systems (1999)

  2. No Access

    Article

    WebSail: From On-line Learning to Web Search

    In this paper we report our research on building WebSail, an intelligent web search engine that is able to perform real-time adaptive learning. WebSail learns from the user's relevance feedback, so that it is abl...

    Zhixiang Chen, **annong Meng, Binhai Zhu… in Knowledge and Information Systems (2002)

  3. No Access

    Article

    Concept Hierarchy-Based Text Database Categorization

    Document categorization as a technique to improve the retrieval of useful documents has been extensively investigated. One important issue in a large-scale metasearch engine is to select text databases that ar...

    Weiyi Meng, Wenxian Wang, Hongyu Sun, Clement Yu in Knowledge and Information Systems (2002)

  4. No Access

    Book and Conference Proceedings

    Advanced Data Mining and Applications

    5th International Conference, ADMA 2009, Bei**g, China, August 17-19, 2009. Proceedings

    Ronghuai Huang, Qiang Yang, Jian Pei… in Lecture Notes in Computer Science (2009)

  5. No Access

    Chapter and Conference Paper

    Alleviating Cold-Start Problem by Using Implicit Feedback

    Collaborative Filter (CF) methods supply favorably personalized predictions relying on adequate data from users. But the ratings, of new users or about new items are not always available and CF can’t make a pr...

    Lei Zhang, **ang-Wu Meng, Jun-Liang Chen… in Advanced Data Mining and Applications (2009)

  6. No Access

    Chapter and Conference Paper

    A Heuristic Algorithm Based on Iteration for Semantic Telecommunications Service Discovery

    How to discover the suited telecommunications service more quickly is important for improving the user experience. In the field of semantic web service most of discovery algorithms pay attention to the precisi...

    Dong Cao, **aofeng Li, **uquan Qiao, Luoming Meng in Web Information Systems and Mining (2009)

  7. No Access

    Chapter and Conference Paper

    Kernel-Based Transductive Learning with Nearest Neighbors

    In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this paper, we aim to solve the classi...

    Liangcai Shu, **hui Wu, Lei Yu, Weiyi Meng in Advances in Data and Web Management (2009)

  8. No Access

    Chapter and Conference Paper

    Identifying and Ranking Possible Semantic and Common Usage Categories of Search Engine Queries

    In this paper, we propose a method for identifying and ranking possible categories of any user query based on the meanings and common usages of the terms and phrases within the query. Our solution utilizes Wor...

    Reza Taghizadeh Hemayati, Weiyi Meng… in Web Information Systems Engineering – WISE… (2010)

  9. No Access

    Chapter and Conference Paper

    mNIR: Diversifying Search Results Based on a Mixture of Novelty, Intention and Relevance

    Current search engines do not explicitly take different meanings and usages of user queries into consideration when they rank the search results. As a result, they tend to retrieve results that cover the most ...

    Reza Taghizadeh Hemayati… in Web Information Systems Engineering - WISE… (2012)

  10. No Access

    Chapter and Conference Paper

    Panoramic Image Search by Similarity and Adjacency for Similar Landscape Discovery

    In this paper, we propose a new image search method, called “panoramic image search”, and show its application to similar landscape discovery. In order to perform the “panoramic image search”, we introduce an ...

    Meng Zhao, Hiroaki Ohshima, Katsumi Tanaka in Web Information Systems Engineering - WISE… (2012)

  11. No Access

    Article

    Exploring heterogeneous information networks and random walk with restart for academic search

    In this paper, we explore heterogenous information networks in which each vertex represents one entity and the edges reflect linkage relationships. Heterogenous information networks contain vertices of several...

    Meng-Fen Chiang, Jiun-Jiue Liou, Jen-Liang Wang… in Knowledge and Information Systems (2013)

  12. No Access

    Article

    A masking index for quantifying hidden glitches

    Data glitches are errors in a dataset. They are complex entities that often span multiple attributes and records. When they co-occur in data, the presence of one type of glitch can hinder the detection of anot...

    Laure Berti-Équille, Ji Meng Loh, Tamraparni Dasu in Knowledge and Information Systems (2015)

  13. No Access

    Article

    Mining and clustering mobility evolution patterns from social media for urban informatics

    In this paper, given a set of check-in data, we aim at discovering representative daily movement behavior of users in a city. For example, daily movement behavior on a weekday may show users moving from one to...

    Chien-Cheng Chen, Meng-Fen Chiang, Wen-Chih Peng in Knowledge and Information Systems (2016)

  14. No Access

    Article

    Inferring lockstep behavior from connectivity pattern in large graphs

    Given multimillion-node graphs such as “who-follows-whom”, “patent-cites-patent”, “user-likes-page” and “actor/director-makes-movie” networks, how can we find unexpected behaviors? When companies operate on th...

    Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos… in Knowledge and Information Systems (2016)

  15. No Access

    Article

    Large-scale supervised similarity learning in networks

    The problem of similarity learning is relevant to many data mining applications, such as recommender systems, classification, and retrieval. This problem is particularly challenging in the context of networks,...

    Shiyu Chang, Guo-Jun Qi, Yingzhen Yang… in Knowledge and Information Systems (2016)

  16. No Access

    Article

    Top-k coupled keyword recommendation for relational keyword queries

    Providing top-k typical relevant keyword queries would benefit the users who cannot formulate appropriate queries to express their imprecise query intentions. By extracting the semantic relationships both between...

    **angfu Meng, Longbing Cao, **aoyan Zhang, **gyu Shao in Knowledge and Information Systems (2017)

  17. No Access

    Article

    Adaptive query relaxation and top-k result ranking over autonomous web databases

    Internet users may suffer the empty or too little answer problem when they post a strict query to the Web database. To address this problem, we develop a general framework to enable automatically query relaxat...

    **angfu Meng, **aoyan Zhang, Yanhuan Tang… in Knowledge and Information Systems (2017)

  18. No Access

    Article

    Answering why-not questions on SPARQL queries

    SPARQL, the W3C standard for RDF query languages, has gained significant popularity in recent years. An increasing amount of effort is currently being exerted to improve the functionality and usability of SPAR...

    Meng Wang, Jun Liu, Bifan Wei, Siyu Yao, Hongwei Zeng… in Knowledge and Information Systems (2019)

  19. No Access

    Article

    Structured query construction via knowledge graph embedding

    In order to facilitate the accesses of general users to knowledge graphs, an increasing effort is being exerted to construct graph-structured queries of given natural language questions. At the core of the con...

    Ruijie Wang, Meng Wang, Jun Liu, Michael Cochez… in Knowledge and Information Systems (2020)

  20. No Access

    Article

    Precise temporal slot filling via truth finding with data-driven commonsense

    The task of temporal slot filling (TSF) is to extract values of specific attributes for a given entity, called “facts”, as well as temporal tags of the facts, from text data. While existing work denoted the te...

    Xueying Wang, Meng Jiang in Knowledge and Information Systems (2020)

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