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Skip to Search Results- 5Community Mining
- 4Social Network Analysis
- 2Community Detection
- 1Community Discovery
- 1Data Mining
- 1Deterministic and Uncertain Networks
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Fall 2020
Many structures in different areas of science can be modeled with graphs containing nodes and edges, which represent the entities of the model and the relationship between them, respectively. Community detection and discovery are two important tasks in Social Network Analysis, which try to find...
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Fall 2015
Information networks that describe the relationship between individuals are called social networks and are usually modeled by a graph structure. Social network analysis is the study of these information networks which leads to uncovering patterns of interaction among the entities. Community...
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Fall 2010
Information networks represent relations in data, relationships typically ignored in iid (independent and identically distributed) data. Such networks abound, like coauthorships in bibliometrics, cellphone call graphs in telecommunication, students interactions in Education, etc. A large body of...
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Fall 2010
Much structured data of scientific interest can be represented as networks, where sets of nodes or vertices are joined together in pairs by links or edges. Although these networks may belong to different research areas, there is one property that many of them do have in common: the network...
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Fall 2018
There is no shortage of community mining algorithms for discovering structure in complex information networks; most with unique advantages, however, all with drawbacks, including efficiency, correctness, resolution limit, and field of view limit. We introduce a novel efficient approach for...
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Fall 2022
Topic modelling seeks to uncover the conceptual and thematic content of collections of documents. These topics can be used as features for document indexing and classification. However, topic models are increasingly important as tools of applied research. As we seek to develop agents capable of...