Clustering is an important technique for mining the intrinsic community structures in networks. The density-based network clustering method is able to not only detect communities of arbitrary size and shape, but also identify hubs and outliers. However, it requires manual parameter specification to define clusters, and is sensitive to the parameter of density threshold which […]
Moderated Group Authoring System for Campus-Wide Workgroups
This paper describes the design and implementation of a file system-based distributed authoring system for campus-wide workgroups. We focus on documents for which changes by different group members are harder to automatically reconcile into a single version. Prior approaches relied on using group-aware editors. Others built collaborative middleware that allowed the group members to use […]
Saturn: Range Queries, Load Balancing and Fault Tolerance in DHT Data Systems
In this paper, we present Saturn, an overlay architecture for large-scale data networks maintained over Distributed Hash Tables (DHTs) that efficiently processes range queries and ensures access load balancing and fault-tolerance. Placing consecutive data values in neighboring peers is desirable in DHTs since it accelerates range query processing; however, such a placement is highly susceptible […]
Weakly Supervised Joint Sentiment-Topic Detection from Text
Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework called joint sentiment-topic (JST) model based on latent Dirichlet allocation (LDA), which detects sentiment and topic simultaneously from text. A reparameterized version of the […]