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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Improving E-Commerce Product Recommendation Using Semantic Context And Sequential Historical Purchases, Mahreen Nasir, C. I. Ezeife, Abdulrauf Gidado
Improving E-Commerce Product Recommendation Using Semantic Context And Sequential Historical Purchases, Mahreen Nasir, C. I. Ezeife, Abdulrauf Gidado
Computer Science Publications
Collaborative Filtering (CF)-based recommendation methods suffer from (i) sparsity (have low user–item interactions) and (ii) cold start (an item cannot be recommended if no ratings exist). Systems using clustering and pattern mining (frequent and sequential) with similarity measures between clicks and purchases for next-item recommendation cannot perform well when the matrix is sparse, due to rapid increase in number of items. Additionally, they suffer from: (i) lack of personalization: patterns are not targeted for a specific customer and (ii) lack of semantics among recommended items: they can only recommend items that exist as a result of a matching rule generated …
Mining Twitter Sequences Of Product Opinions With Multi-Word Aspect Terms, Vinay Kiran Manjunath
Mining Twitter Sequences Of Product Opinions With Multi-Word Aspect Terms, Vinay Kiran Manjunath
Electronic Theses and Dissertations
Social media platforms have opened doors to users' opinions and perceptions. The text remains the most popular means of contact on social media, despite different means of communication (audio/video and images). Twitter is one such microblogging platform that allows people to express their thoughts within 280 characters per message. The freedom of expression has made it difficult to understand the polarity (Positive, Negative, or Neutral) of the tweets/posts. Given a corpus of microblog texts (e.g., "the new iPhone battery life is good, but camera quality is bad"), mining aspects (e.g., battery life, camera quality) and opinions (e.g., good, bad) of …