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13 Result(s)

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  1. No Access

    Chapter and Conference Paper

    Counting Edges and Triangles in Online Social Networks via Random Walk

    Online social network (OSN) analysis has attracted much attention in recent years. Edge and triangle counts are both fundamental properties in OSNs. However, for many OSNs, one can only access parts of the net...

    Yang Wu, Cheng Long, Ada Wai-Chee Fu, Zitong Chen in Web and Big Data (2017)

  2. No Access

    Chapter and Conference Paper

    Community Based Information Dissemination

    Given a social network, we study the problem of finding \(k\) seeds that maximize the dissemination of information. B...

    Zhengwei Yang, Ada Wai-Chee Fu, Yanyan Xu, Silu Huang… in Databases Theory and Applications (2015)

  3. No Access

    Chapter and Conference Paper

    Mining N-most Interesting Itemsets

    Previous methods on mining association rules require users to input a minimum support threshold. However, there can be too many or too few resulting rules if the threshold is set inappropriately. It is difficu...

    Ada Wai-chee Fu, Renfrew Wang-wai Kwong, Jian Tang in Foundations of Intelligent Systems (2010)

  4. Chapter and Conference Paper

    Workshop Organizers’ Message

    International Workshop on Privacy-Preserving Data Analysis (PPDA) 2009 took place at Brisbane, Australia on 21st April, 2009. There were two sessions for this workshop with 2 paper presentations in the first s...

    Raymond Chi-Wing Wong, Ada Wai-Chee Fu in Database Systems for Advanced Applications (2009)

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  5. No Access

    Chapter

    Privacy-Preserving Data Stream Classification

    In a wide range of applications, multiple data streams need to be examined together in order to discover trends or patterns existing across several data streams. One common practice is to redirect all data str...

    Yabo Xu, Ke Wang, Ada Wai-Chee Fu, Rong She, Jian Pei in Privacy-Preserving Data Mining (2008)

  6. No Access

    Chapter and Conference Paper

    Clustering Massive Text Data Streams by Semantic Smoothing Model

    Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organization and topic detection and tracing e...

    Yubao Liu, Jiarong Cai, Jian Yin, Ada Wai-Chee Fu in Advanced Data Mining and Applications (2007)

  7. No Access

    Chapter and Conference Paper

    Finding Time Series Discords Based on Haar Transform

    The problem of finding anomaly has received much attention recently. However, most of the anomaly detection algorithms depend on an explicit definition of anomaly, which may be impossible to elicit from a doma...

    Ada Wai-chee Fu, Oscar Tat-Wing Leung… in Advanced Data Mining and Applications (2006)

  8. No Access

    Chapter and Conference Paper

    Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures

    Individual privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view of k-anonymity is clustering with a constr...

    Jiuyong Li, Raymond Chi-Wing Wong… in Data Warehousing and Knowledge Discovery (2006)

  9. No Access

    Chapter and Conference Paper

    ISM: Item Selection for Marketing with Cross-Selling Considerations

    Many different algorithms are studied on association rules in the literature of data mining. Some researchers are now focusing on the application of association rules. In this paper, we will study one of the a...

    Raymond Chi-Wing Wong, Ada Wai-Chee Fu in Advances in Knowledge Discovery and Data Mining (2004)

  10. No Access

    Chapter and Conference Paper

    Mining Frequent Episodes for Relating Financial Events and Stock Trends

    It is expected that stock prices can be affected by the local and overseas political and economic events. We extract events from the financial news of Chinese local newspapers which are available on the web, t...

    Anny Ng, Ada Wai-chee Fu in Advances in Knowledge Discovery and Data Mining (2003)

  11. No Access

    Chapter and Conference Paper

    Enhancing Effectiveness of Outlier Detections for Low Density Patterns

    Outlier detection is concerned with discovering exceptional behaviors of objects in data sets. It is becoming a growingly useful tool in applications such as credit card fraud detection, discovering criminal b...

    Jian Tang, Zhixiang Chen, Ada Wai-chee Fu… in Advances in Knowledge Discovery and Data M… (2002)

  12. No Access

    Chapter and Conference Paper

    Optimal Algorithms for Finding User Access Sessions from Very Large Web Logs

    Although efficient identification of user access sessions from very large web logs is an unavoidable data preparation task for the success of higher level web log mining, little attention has been paid to algo...

    Zhixiang Chen, Ada Wai-Chee Fu… in Advances in Knowledge Discovery and Data M… (2002)

  13. No Access

    Chapter and Conference Paper

    Discovering Temporal Patterns for Interval-based Events

    In many daily transactions, the time when an event takes place is known and stored in databases. Examples range from sales records, stock exchange, patient records, to scientific databases in geophysics and as...

    Po-shan Kam, Ada Wai-chee Fu in Data Warehousing and Knowledge Discovery (2000)