Extraction of aspects of goods and services from consumers reviews using conditional random fields model
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Abstract
This paper describes the Information extraction system that was presented at SentiRuEval-2015: aspect-based sentiment analysis of users' reviews in Russian. The proposed system uses a conditional random field algorithm to extract aspect terms mentioned in the text. A set of morphological features was used for machine learning. The system intent to perform two subtasks, Task A – automatic extraction of explicit aspects and Task B – automatic extraction of all aspects (explicit, implicit and sentiment facts), and tested on two domains: restaurants and automobiles. Our systems performed competitively and showed the results comparable to those of the other 10 participants.
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References
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