Title :
Automatic Extract Product-Entity from Untagged Review
Author :
Li, Rongjun ; Wang, Xiaojie ; Cen, Songxiang ; Mao, Yu
Author_Institution :
Sch. of Compute Sci. & Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
fDate :
Nov. 30 2009-Dec. 1 2009
Abstract :
In this paper, we present a new method to extract product entity from Chinese customer reviews. The approach requires no segmentation, no domain dictionary and little prior domain knowledge, which is more suitable for domain with resource-limited. Quite different from the previous work, the proposed method first get the entity candidates use a general version bootstrapping algorithm and then distribute the credits from the seed entities to other entity candidates based on graph´s topology structure. Experiments on COAE2008 corpus shows that the method proposed here is effective.
Keywords :
feature extraction; graph theory; natural language processing; COAE2008 corpus; Chinese customer reviews; automatic extract product-entity; bootstrapping algorithm; graph topology structure; product extraction; untagged review; Dictionaries; Engines; Humans; Knowledge acquisition; Natural languages; Speech analysis; Telecommunication computing; Tellurium; Terminology; Topology; Entity extraction; Natural language processing;
Conference_Titel :
Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3888-4
DOI :
10.1109/KAM.2009.79