Name
Title | ||
|---|---|---|
Mining Compatible/Incompatible Entities from Question and Answering via Yes/No Answer Classification using Distant Label Expansion. |
Abstract | ||
|---|---|---|
Product Community Question Answering (PCQA) provides useful information about products and their features (aspects) that may not be well addressed by product descriptions and reviews. We observe that a productu0027s compatibility issues with other products are frequently discussed in PCQA and such issues are more frequently addressed in accessories, i.e., via a yes/no question Does this mouse work with windows 10?. In this paper, we address the problem of extracting compatible and incompatible products from yes/no questions in PCQA. This problem can naturally have a two-stage framework: first, we perform Complementary Entity (product) Recognition (CER) on yes/no questions; second, we identify the polarities of yes/no answers to assign the complementary entities a compatibility label (compatible, incompatible or unknown). We leverage an existing unsupervised method for the first stage and a 3-class classifier by combining a distant PU-learning method (learning from positive and unlabeled examples) together with a binary classifier for the second stage. The benefit of using distant PU-learning is that it can help to expand more implicit yes/no answers without using any human annotated data. We conduct experiments on 4 products to show that the proposed method is effective. |
Year | Venue | Field |
|---|---|---|
2016 | arXiv: Computation and Language | Question answering,Binary classification,Compatibility (mechanics),Computer science,Natural language processing,Artificial intelligence,Classifier (linguistics) |
DocType | Volume | Citations |
Journal | abs/1612.04499 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hu Xu | 1 | 48 | 7.57 |
| Lei Shu | 2 | 0 | 2.03 |
| Jingyuan Zhang | 3 | 0 | 2.70 |
| Philip S. Yu | 4 | 30670 | 3474.16 |