Sciweavers

Share
SIGIR
2006
ACM

Answering complex questions with random walk models

9 years 8 months ago
Answering complex questions with random walk models
We present a novel framework for answering complex questions that relies on question decomposition. Complex questions are decomposed by a procedure that operates on a Markov chain, by following a random walk on a bipartite graph of relations established between concepts related to the topic of a complex question and subquestions derived from topic-relevant passages that manifest these relations. Decomposed questions discovered during this random walk are then submitted to a state-of-the-art Question Answering (Q/A) system in order to retrieve a set of passages that can later be merged into a comprehensive answer by a Multi-Document Summarization (MDS) system. In our evaluations, we show that access to the decompositions generated using this method can significantly enhance the relevance and comprehensiveness of summarylength answers to complex questions. Categories and Subject Descriptors H.3.m [INFORMATION STORAGE AND RETRIEVAL]: Miscellaneous; I.2.7 [ARTIFICIAL INTELLIGENCE]: Natur...
Sanda M. Harabagiu, V. Finley Lacatusu, Andrew Hic
Added 14 Jun 2010
Updated 14 Jun 2010
Type Conference
Year 2006
Where SIGIR
Authors Sanda M. Harabagiu, V. Finley Lacatusu, Andrew Hickl
Comments (0)
books