Browsing 08 Information and Computing Sciences by Title

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Browsing 08 Information and Computing Sciences by Title

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  • Zhang, P; Zhu, X; Guo, L (IEEE Computer Society, 2009-01)
    In this paper, we propose a framework to build prediction models from data streams which contain both labeled and unlabeled examples. We argue that due to the increasing data collection ability but limited resources for ...
  • Wan, L; Chen, L; Zhang, C (IEEE Computer Society Press, 2013-01)
    In this paper, we focus on the problem of mining Probabilistic Dependent Frequent Serial Episodes (P-DFSEs) from uncertain sequence data. By observing that the frequentness probability of an episode in an uncertain sequence ...
  • Lin, L; Luo, D; Liu, L (Springer, 2005-01)
    There have been many technical trading rules in stock market since the first stock exchange founded. Along with the developing of computer technology, the technical trading rules are playing more and more important roles ...
  • Ou, Y; Cao, L; Luo, C; Liu, L (IEEE Computer Society, 2008-01)
    Market Surveillance plays an important role in maintaining market integrity, transparency and fairnesss. The existing trading pattern analysis only focuses on interday data which discloses explicit and high-level market ...
  • Hsieh, T; Hsiao, H; Yeh, W (Elsevier, 2012-01)
    The 2008 financial tsunami had a serious impact on the economic development of many countries, including Taiwan. Thus, the ability to predict financial failure and their trends is crucial and attracts public and professional ...
  • Zhao, Y; Zhang, H; Figueiredo, F; Cao, L; Zhang, C (ACM, 2007-01)
    Many organisations have their digital information stored in a distributed systems structure scheme, be it in different locations, using vertically and horizontally distributed repositories, which brings about an high level ...
  • Guo, J; Zhang, P; Tan, J; Guo, L (ACM, 2011-01)
    Mining frequent patterns from data streams has drawn increasing attention in recent years. However, previous mining algorithms were all focused on a single data stream. In many emerging applications, it is of critical ...
  • Fariha, A; Ahmed, CF; Leung, CK; Abdullah, SM; Cao, L (Springer, 2013-01)
    In modern life, interactions between human beings frequently occur in meetings, where topics are discussed. Semantic knowledge of meetings can be revealed by discovering interaction patterns from these meetings. An existing ...
  • Li, X; Zhang, L; Chen, E; Zong, Y; Xu, G (Springer Berlin / Heidelberg, 2013-01)
    It is common today for users to print the informative information from webpages due to the popularity of printers and internet. Thus, many web printing tools such as Smart Print and PrintUI are developed for online printing. ...
  • Wan, L; Chen, L; Zhang, C (2013)
    Data uncertainty has posed many unique challenges to nearly all types of data mining tasks, creating a need for uncertain data mining. In this paper, we focus on the particular task of mining probabilistic frequent serial ...
  • Zhang, S; You, X; Jin, Z; Wu, X (2009-10)
    When extracting knowledge (or patterns) from multiple databases, the data from different databases might be too large in volume to be merged into one database for centralized mining on one computer, the local information ...
  • Cao, L; Zhao, Y; Figueiredo, F; Ou, Y; Luo, D (Springer, 2007-01)
    In the real world, exceptional behavior can be seen in many situations such as security-oriented fields. Such behavior is rare and dispersed, while some of them may be associated with significant impact on the society. A ...
  • Guo, J; Zhang, P; Tan, J; Guo, L (Elsevier, 2012-01)
    Mininghottopicsfrom twitter streamshas attractedalotof attentionin recent years.Traditionalhottopicmining from InternetWeb pages were mainly basedontext clustering.However, comparedtothetextsinWeb pages, twitter texts are ...
  • Yang, Y; Wu, X; Zhu, X (Springer, 2006-01)
    Prediction in streaming data is an important activity in the modern society. Two major challenges posed by data streams are (1) the data may grow without limit so that it is difficult to retain a long history of raw data; ...
  • Lin, L; Cao, L (Inderscience Publishers, 2008-01)
    Stock trading plays an important role for supporting profitable stock investment. In particular, more and more data mining-based technical trading rules have been developed and used in stock trading systems to assist ...
  • Feng, L; Dillon, TS (Springer-Verlag Berlin, 2005-01)
    XML-enabled association rule framework [FDWC03] extends the notion of associated items to XML fragments to present associations among trees rather than simple-structured items of atomic values. They are more flexible and ...
  • Zhang, J; Zhu, X; Li, X; Zhang, S (2013)
    Recommender systems can predict individual user's preference (individual rating) on items by examining similar items' popularity or similar users' taste. However, these systems cannot tell item's long-term popularity. In ...
  • Lo, D; Li, J; Wong, L; Khoo, S (IEEE Computer Soc, 2011-01)
    Billions of dollars are spent annually on software-related cost. It is estimated that up to 45 percent of software cost is due to the difficulty in understanding existing systems when performing maintenance tasks (i.e., ...
  • Wang, C; Lu, J; Zhang, G (2007-08)
    Web content mining aims to discover useful information and generate desired knowledge from a large amount of web pages. Key information, such as distinctive menu items, navigation indicators, which is embedded in web pages, ...
  • Mao, G; Wu, X; Zhu, X; Chen, G; Liu, C (Sage Publications Ltd, 2007-01)
    Frequent pattern mining from data streams is an active research topic in data mining. Existing research efforts often rely on a two-phase framework to discover frequent patterns: (1) using internal data structures to store ...