<--- Back to Details
First PageDocument Content
Computational linguistics / Information retrieval / Natural language processing / Power Architecture / Watson / Artificial intelligence applications / IBM / Jeopardy! / Open domain question answering / Science / Computing / Information science
Date: 2011-09-26 02:30:26
Computational linguistics
Information retrieval
Natural language processing
Power Architecture
Watson
Artificial intelligence applications
IBM
Jeopardy!
Open domain question answering
Science
Computing
Information science

Building Watson A Brief Overview of the DeepQA Project

Add to Reading List

Source URL: www.cs.hku.hk

Download Document from Source Website

File Size: 1,56 MB

Share Document on Facebook

Similar Documents

Open-Domain Web-Based List Question Answering with LX-ListQuestion Patricia Nunes Gonçalves, António Branco University of Lisbon Edifício C6, Departamento de Informática Faculdade de Ciências, Universidade de Lisboa

DocID: 1rYko - View Document

Document retrieval / Query expansion / Search engine indexing / Open domain question answering / Relevance / Full text search / XML-Retrieval / Information science / Information retrieval / Relevance feedback

Queripidia: Query-specific Wikipedia Construction Laura Dietz University of Massachusetts Amherst, MA, U.S.A.

DocID: 1gpIw - View Document

Natural language processing / Information science / Information retrieval / Question answering / Human communication / Question / Yes and no / Subject / Open domain question answering / Computational linguistics / Science / Linguistics

Question Answering with Lydia (TREC 2005 QA track) Jae Hong Kil, Levon Lloyd, and Steven Skiena Department of Computer Science State University of New York at Stony Brook Stony Brook, NY

DocID: 18Ld9 - View Document

Computational linguistics / Natural language processing / Question answering / Open domain question answering / Boris Katz / Text Retrieval Conference / Cyc / Document retrieval / Question / Information science / Information retrieval / Science

Question Answering from the Web Using Knowledge Annotation and Knowledge Mining Techniques Jimmy Lin and Boris Katz MIT Computer Science and Artificial Intelligence Laboratory 200 Technology Square Cambridge, Massachuset

DocID: 18I3B - View Document

Information retrieval / Computational linguistics / Question answering / Text Retrieval Conference / Yahoo! Answers / Okapi BM25 / Question / Yes and no / Open domain question answering / Natural language processing / Information science / Science

Building a Foundation System for Producing Short Answers to Factual Questions Sameer S. Pradhan* , Gabriel Illouz†§ , Sasha J. Blair-Goldensohn† , Andrew Hazen Schlaikjer† , Valerie Krugler* , Elena Filatova† ,

DocID: 18HsX - View Document