Joel Acevedo-Aviles

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The challenge of associating entities across multiple domains is a key problem in social media understanding. Successful cross-domain entity resolution provides integration of information from multiple sites to create a complete picture of user and community activities, characteristics, and trends. In this work, we examine the problem of entity resolution(More)
The wide availability of signal processing and language tools to extract structured data from raw content has created a new opportunity for the processing of structured signals. In this work, we explore models for the simulation and recognition of scenarios—i.e., time sequences of structured data. For simulation, we construct two models—hidden(More)
In this demo paper we introduce VizLinc; an open-source software suite that integrates automatic information extraction, search, graph analysis, and geo-location for interactive visualization and exploration of large data sets. VizLinc helps users in: 1) understanding the type of information the data set under study might contain, 2) finding patterns and(More)
Machine learning methods in Human Language Technology have reached a stage of maturity where widespread use is both possible and desirable. The MIT Lincoln Laboratory LLTools software suite provides a step towards this goal by providing a set of easily accessible frameworks for incorporating speech, text, and entity resolution components into larger(More)
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