融合词语义表示和新词发现的领域本体演化——以产品评论数据为例

Integrating Word Semantic Representation and New Word Identification for Domain Ontology Evolution:A Case Study of Product Online Reviews

[目的/意义]针对传统本体演化中对新知识和新需求的捕捉存在不准确、低效率的问题,提出一种基于领域新词发现的本体演化方法,并以用户产品评论数据为例进行验证.[方法/过程]首先采用自然语言处理算法对用户产品评论文本语料进行文本预处理,并利用Word2vec算法进行词向量嵌入;然后采用深度学习中Bi-LSTM-Atten-tion-CRF算法实现候选领域新词的识别和抽取,并利用K-means算法进行聚类以得到最终领域新词;最后利用本体演化的六阶段演化流程,实现领域本体的演化工作.[结果/结论]以智能手机领域产品评论为实验数据,验证了本研究采用领域新词发现模型具有更高的准确率和召回率,由此演化得到智能手机领域新版产品本体.领域新版产品本体既可以帮助产品设计者根据领域本体中新特征、新功能优化产品设计,也可以支持消费者利用产品评论进行购买决策.

[Purpose/significance]Due to the inaccuracy and low efficiency in capturing new knowledge andnew requirements in traditional ontology evolution,based on domain new word identification,an ontology evolutionmethod is proposed and evaluated by analyzing a large volume of product online reviews.[Method/process]First,a series of natural language processing algorithms were used to pre-process product review text corpus,and theWord2vec algorithm was adopted for word vector embedding.Then,a Bi-ILSTM-Attention-CRF algorithm was utilizedfor the recognition and extraction of new words in a candidate set,and the K-means algorithm was applied for cluste-ring to get the final domain new words.Finally,the Six-Stage evolution process of ontology evolution was invited foranalyzing domain ontology evolution.[Result/conclusion]By analyzing smart phone reviews as examples,it can befound that the proposed approach about new word identification presents a higher accuracy and recall rate and a newversion of the product ontology in the smart phone domain can be evolved accordingly.It helps designers to optimizefeature and function configuration in new product development and consumers to analyze online opinions for purchasedecisions.