Question answering can help us make sense of Big Data by reducing a massive collection of documents into a relevant answer. Knowledge bases constructed automatically from the Web are rich sources of answers, but they suffer from sparsity in the relations that connect entities. For example, we can express that a person studied at a university by saying “studied at”, “was a student of”, or “graduated from”. We’re developing scalable techniques to recognize paraphrases and make knowledge bases more accessible to question answering systems.
Presenter: Alvaro Morales