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  • Influence
TwitterRank: finding topic-sensitive influential twitterers
TLDR
Experimental results show that TwitterRank outperforms the one Twitter currently uses and other related algorithms, including the original PageRank and Topic-sensitive PageRank, which is proposed to measure the influence of users in Twitter. Expand
Comparing Twitter and Traditional Media Using Topic Models
TLDR
This paper empirically compare the content of Twitter with a traditional news medium, New York Times, using unsupervised topic modeling, and finds interesting and useful findings for downstream IR or DM applications. Expand
Detecting product review spammers using rating behaviors
TLDR
This paper identifies several characteristic behaviors of review spammers and model these behaviors so as to detect the spammers, and shows that the detected spammers have more significant impact on ratings compared with the unhelpful reviewers. Expand
Measuring article quality in wikipedia: models and evaluation
TLDR
This paper proposes three article quality measurement models that make use of the interaction data between articles and their contributors derived from the article edit history and proposes a model that combines partial reviewership of contributors as they edit various portions of the articles. Expand
Hierarchical text classification and evaluation
  • Aixin Sun, Ee-Peng Lim
  • Mathematics, Computer Science
  • Proceedings IEEE International Conference on…
  • 29 November 2001
Hierarchical classification refers to the assignment of one or more suitable categories from a hierarchical category space to a document. While previous work in hierarchical classification focused onExpand
Mobile Commerce: Promises, Challenges and Research Agenda
TLDR
An overview of mobile Commerce development is presented by examining the enabling technologies, the impact of mobile commerce on the business world, and the implications to mobile commerce providers. Expand
Analyzing feature trajectories for event detection
We consider the problem of analyzing word trajectories in both time and frequency domains, with the specific goal of identifying important and less-reported, periodic and aperiodic words. A set ofExpand
Predicting trusts among users of online communities: an epinions case study
TLDR
A taxonomy is developed to obtain an extensive set of relevant features derived from user attributes and user interactions in an online community and empirical results show that the trust among users can be effectively predicted using pre-trained classifiers. Expand
Topical Keyphrase Extraction from Twitter
TLDR
A context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking are proposed. Expand
Dynamic Web Service Selection for Reliable Web Service Composition
TLDR
This paper studies the dynamic web service selection problem in a failure-prone environment and proposes two strategies to select Web services that are likely to successfully complete the execution of a given sequence of operations. Expand
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