Abstract
With the development of web data integration, it poses a new challenge how to match relevant reviews to integrated database objects and provide users the more complete holistic views of entities. According to the features of web data integration and reviews from web, we proposed a method based on 2-layer Conditional Random Fields(CRF) to match reviews to database objects. On the one hand, our method leverages the integrated structured entity and significantly reduces the dependence on manually labeled training data. On the other hand, we employ semi-Markov CRF to recognize the structured entities and exploit a variety of entity-level and pattern-level recognition clues available in a database of entities and labeled reviews, thereby effectively resolving the entity variety and improving the accuracy of the entity recognition. Experiments in multiple domains show that our method can substantially superior to traditional tf-idf based methods as well as a recent language model-based method for the review matching problem.
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Yongxin, Z., Qingzhong, L., Dequan, W., Yanhui, D., Congli, L., Zhongmin, Y. (2015). Matching Reviews to Object Based on 2-Stage CRF. In: Cheng, R., Cui, B., Zhang, Z., Cai, R., Xu, J. (eds) Web Technologies and Applications. APWeb 2015. Lecture Notes in Computer Science(), vol 9313. Springer, Cham. https://doi.org/10.1007/978-3-319-25255-1_8
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DOI: https://doi.org/10.1007/978-3-319-25255-1_8
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