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Modeling socialness in dynamic social networks

Socialness refers to the ability to elicit social interaction and social links among people. It is a concept often associated with individuals. Although there are tangible benefits in socialness, there is little research in its modeling. In this …

Topical keyphrase extraction from Twitter

Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a …

On Modeling Virality of Twitter Content

Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan …

Improving diversity of focused summaries through the negative endorsements of redundant facts

We present NegativeRank, a novel graph-based sentence ranking model to improve the diversity of focused summary by performing random walks over sentence graph with negative edge weights. Unlike the typical eigenvector centrality ranking, our method …

Answer diversification for complex question answering on the web

We present a novel graph ranking model to extract a diverse set of answers for complex questions via random walks over a negative-edge graph. We assign a negative sign to edge weights in an answer graph to model the redundancy relation among the …

Probabilistic models for topic learning from images and captions in online biomedical literatures

Biomedical images and captions are one of the major sources of information in online biomedical publications. They often contain the most important results to be reported, and provide rich information about the main themes in published papers. In the …

Using Negative Voting to Diversify Answers in Non-factoid Question Answering

We propose a ranking model to diversify answers of non-factoid questions based on an inverse notion of graph connectivity. By representing a collection of candidate answers as a graph, we posit that novelty, a measure of diversity, is inversely …

AskDragon: A redundancy-based factoid question answering system with lightweight local context analysis

We introduce our QA system AskDragon which employs a novel lightweight local context analysis technique to handling two broad classes of factoid questions, entity and numeric questions. The local context analysis module dramatically improves the …

Addressing the variability of natural language Expression in sentence similarity with semantic structure of the sentences

In this paper, we present a new approach that incorporates semantic structure of sentences, in a form of verb-argument structure, to measure semantic similarity between sentences. The variability of natural language expression makes it difficult for …

Utilizing Semantic, Syntactic, and Question category Information for Automated Digital Reference Services

Digital reference services normally rely on human experts to provide quality answers to the user requests via online communication tools. As the services gain more popularity, more experts are needed to keep up with a growing demand. Alternatively, …