Question Answering for Alzheimer Disease Using Information Retrieval

The some- what unusual multiple-choice nature of this question answering task meant that we were able to attempt interesting transformations of questions by inserting answer graphs

Each T-H pair identified for each answer option corresponding to a question is now assigned a score based on the NER module, Textual Entailment module,

We investigated two forms of information expansion to improve over this baseline: (1) statistical expansion of the test document with sentences from the topical background corpus,

Table 2 instead presents the statistical correlation of the language used in the search query and the language used in the User Interface; from the experimental evidence emerges

Our participation at ResPubliQA 2010 was based on applying an In- formation Retrieval (IR) engine of high performance and a validation step for removing incorrect answers.. The

For the first run, we simply returned, for each question, the highest scored gist sentence found in the topic-oriented summarization mode for the complete data collection

Applying our logistic model using both the rank and the document score as explanatory variables, the resulting mean average precision is clearly better than the round-robin

The goal is threefolds: (1) create confidence area for information search by community detection based on tags similarity (2) introduce a new notion of Social Document Profile based