Open Access
ARTICLE
Answer Classification via Machine Learning in Community Question Answering
Yue Jiang, Xinyu Zhang, Wohuan Jia, Li Xu*
College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, China
* Corresponding Author: Li Xu. Email:
Journal on Artificial Intelligence 2021, 3(4), 163-169. https://doi.org/10.32604/jai.2021.027590
Received 21 January 2022; Accepted 25 January 2022; Issue published 07 February 2022
Abstract
As a new type of knowledge sharing platform, the community question
answer website realizes the acquisition and sharing of knowledge, and is loved and
sought after by the majority of users. But for multi-answer questions, answer quality
assessment becomes a challenge. The answer selection in CQA (Community
Question Answer) was proposed as a challenge task in the SemEval competition,
which gave a data set and proposed two subtasks. Task-A is to give a question
(including short title and extended description) and its answers, and divide each
answer into absolutely relevant (good), potentially relevant (potential) and bad or
irrelevant (bad, dialog, non-English, other). Task-B is to give a YES/NO type
question (including short title and extended description) and some answers. Based
on the answer of the absolute correlation type (good), judge whether the answer to
the whole question should be yes, no or uncertain. This paper first preprocesses this
data set, and then uses natural language processing technology to perform word
segmentation, part-of-speech tagging and named entity recognition on the data set,
and then perform feature extraction on the preprocessed data set. Finally, SVM and
random forest are used to classify on the basis of feature extraction, and the
classification results are analyzed and compared. The experiments in this paper show
that SVM and random forest methods have good results on the data set, and exceed
the multi-classifier ensemble learning method and hierarchical classification method
proposed by the predecessors.
Keywords
Cite This Article
Y. Jiang, X. Zhang, W. Jia and L. Xu, "Answer classification via machine learning in community question answering,"
Journal on Artificial Intelligence, vol. 3, no.4, pp. 163–169, 2021.