This paper describes our participation in the QA4MRE 2011
task, targeted at reading comprehension tests and multiple choice question
answering. Our system constructs a co-occurrence graph with words
that are common or proper nouns and verbs extracted from each document.
The documents are pre-selected through an information retrieval
process for recovering only those that are most relevant to a particular
question. An algorithm to detect communities of words with signicant
co-occurrence is applied to the co-occurrence graph. Each of the detected
communities are treated as diferent contexts of a question in the corpus,
and these contexts are used to find the most suitable answer. Our
evaluation results suggest that, the number of retrieved documents is an
important factor in the results.