INEX Tweet Contextualization Track at CLEF 2012: Query Reformulation using Terminological Patterns and Automatic Summarization

The tweet contextualization INEX task at CLEF 2012 consists of the developing of a system that, given a tweet, can provide some context about the subject of the tweet, in order to help the reader to understand it. This context should take the form of a readable summary, not exceeding 500 words, composed of passages from a provided Wikipedia corpus. Our general approach to get this objective is the following: we perform some automatic reformulations of the initial tweets provided for the task (obtaining a list of terms related with the main topic of all them using terminological patterns). Then, using these reformulated tweets, we obtain related documents with the search engine Indri. Finally, we use REG, an automatic extractive summarization system based on graphs, to summarize these documents and provide the summary associated to each tweet.