RankCompete: Simultaneous ranking and clustering of information networks
نویسندگان
چکیده
منابع مشابه
RankCompete: Simultaneous ranking and clustering of information networks
Random walk was first introduced by Karl Pearson in 1905 and has inspired many research works in different fields. In recent years, random walk has been adopted in information network research, for example, ranking and similarity estimation. In this paper, we introduce a new model called RankCompte, which allows multiple random walkers in the same network (existing work mostly focus on random w...
متن کاملRanking Information in Networks
Given an information network, we are interested in ranking sets of nodes that score highest on user-specified criteria. Examples include (1) discovering sets of authors with expertise in a wide range of disciplines; (2) finding sets of patents which, if removed, would have the greatest effect on the patent citation network; (3) identifying small sets of IP addresses which taken together account...
متن کاملClustering Attributed Multi-graphs with Information Ranking
Attributed multi-graphs are data structures to model realworld networks of objects which have rich properties/attributes and they are connected by multiple types of edges. Clustering attributed multigraphs has several real-world applications, such as recommendation systems and targeted advertisement. In this paper, we propose an efficient method for Clustering Attributed Multi-graphs with Infor...
متن کاملClustering Top-Ranking Sentences for Information Access
In this paper we propose the clustering of top-ranking sentences (TRS) for effective information access. Top-ranking sentences are selected by a query-biased sentence extraction model. By clustering such sentences, we aim to generate and present to users a personalised information space. We outline our approach in detail and we describe how we plan to utilise user interaction with this space fo...
متن کاملRanking and clustering of nodes in networks with smart teleportation
Random teleportation is a necessary evil for ranking and clustering directed networks based on random walks. Teleportation enables ergodic solutions, but the solutions must necessarily depend on the exact implementation and parametrization of the teleportation. For example, in the commonly used PageRank algorithm, the teleportation rate must trade off a heavily biased solution with a uniform so...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neurocomputing
سال: 2012
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2011.06.038