TY - GEN
T1 - Opinion retrieval from blogs
AU - Zhang, Wei
AU - Yu, Clement
AU - Meng, Weiyi
PY - 2007
Y1 - 2007
N2 - Opinion retrieval is a document retrieval process, which requires documents to be retrieved and ranked according to their opinions about a query topic. A relevant document must satisfy two criteria: relevant to the query topic, and contains opinions about the query, no matter if they are positive or negative. In this paper, we describe an opinion retrieval algorithm. It has a traditional information retrieval (IR) component to find topic relevant documents from a document set, an opinion classification component to find documents having opinions from the results of the IR step, and a component to rank the documents based on their relevance to the query, and their degrees of having opinions about the query. We implemented the algorithm as a working system and tested it using TREC 2006 Blog Track data in automatic title-only runs. Our result showed 28% to 32% improvements in MAP score over the best automatic runs in this 2006 track. Our result is also 13% higher than a state-of-art opinion retrieval system, which is tested on the same data set.
AB - Opinion retrieval is a document retrieval process, which requires documents to be retrieved and ranked according to their opinions about a query topic. A relevant document must satisfy two criteria: relevant to the query topic, and contains opinions about the query, no matter if they are positive or negative. In this paper, we describe an opinion retrieval algorithm. It has a traditional information retrieval (IR) component to find topic relevant documents from a document set, an opinion classification component to find documents having opinions from the results of the IR step, and a component to rank the documents based on their relevance to the query, and their degrees of having opinions about the query. We implemented the algorithm as a working system and tested it using TREC 2006 Blog Track data in automatic title-only runs. Our result showed 28% to 32% improvements in MAP score over the best automatic runs in this 2006 track. Our result is also 13% higher than a state-of-art opinion retrieval system, which is tested on the same data set.
KW - Blog retrieval
KW - Information retrieval
KW - Opinion retrieval
KW - TREC
UR - https://www.scopus.com/pages/publications/56549103813
U2 - 10.1145/1321440.1321555
DO - 10.1145/1321440.1321555
M3 - Conference contribution
SN - 9781595938039
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 831
EP - 840
BT - CIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management
T2 - 16th ACM Conference on Information and Knowledge Management, CIKM 2007
Y2 - 6 November 2007 through 9 November 2007
ER -