基于网络评论情感信任分析的推荐策略

Recommendation Strategy Based on Trust Model via Emotional Analysis of Online Comment

个性化推荐技术已经成为电子商务领域解决信息过载问题的一种有效手段.传统的协同过滤推荐系统由于算法自身的特点,普遍存在数据稀疏性和冷启动等问题,这些问题的存在使得个性化推荐过程中的准确率大大降低,影响了用户的个性化体验和对系统的信心.从社会学中的信任关系角度着手,通过对网络用户在线评论信息进行情感分析,提取出评论信息中用户的情感倾向,并对它进行有效量化,然后通过计算用户情感倾向的相似性建立用户间的信任关系.同时,在推荐过程中将所构建的信任关系与评分数据的相似度进行有效结合,弥补了相似度作为唯一权重因素而导致的推荐准确率降低的不足.首先,基于在线评论信息对用户的情感倾向性进行分析与量化;然后,基于情感相似度对用户信任关系进行建模;最后,基于用户情感信任关系对推荐策略进行设计.在所选数据集上的模拟对比实验表明,改进的引入情感分析信任模型的个性化推荐策略能够有效地降低平均绝对误差值MAE,推荐的准确率得到了提高;同时,覆盖率coverage和推荐系统对商品长尾的发掘能力也得到了有效的提升;另外,信任关系自主管理机制的引入,也大大改善了用户对系统的个性化体验,增强了用户对系统的信心.

Personalized recommendation technology has become a very effective approach to cope with“information overload”in E-commerce.Aiming at the problems of data sparseness and cold-start in traditional collaborative filtering recommender system,which have led to the decline of the accuracy in recommendation,weakened user’s confidence towards the system,this paper proposed a new recommendation strategy using trust theory in sociology to offer users better personalized service.From this perspective,user’s online comments to the items that they have experienced are analyzed,the user’s emotional tendency is extracted,and it is effectively quantified.The trust relationship between users is grown by analyzing the similarity of user’s emotional tendency.At the same time,users’rating data are combined to compensate for the lack of recommendation factor caused by similarity as the only preference weight.The work in this paper includes three parts:analysis and quantification of user emotional tendency based on online reviews,mo-deling of trust relationship based on similarity between emotion and design of recommendation strategy based on trust relationship.Experiments show that the proposed recommendation strategy can effectively reduce the average absolute error value called MAE,which means the recommendation accuracy is improved.At the same time,the coverage rate is also effective increased,which means that the system has more items to recommend.Additionally,the management mechanism of trust relationship can also greatly enhance user’s personalized experience of the system and user’s confidence to the system.