Sentic Computing: Techniques, Tools, and Applications (Paperback)

In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data.

在這本書中，常識計算技術進一步發展並應用於彌合自然語言資料的詞級別和所傳達的概念級別意見之間的語義差距。具體而言，利用圖形挖掘和多維度降維技術的集成應用，對兩個常識知識庫進行開發，以建立一個新穎的開放領域意見挖掘和情感分析智能引擎。所提出的方法稱為情感計算，對文本進行子句級別的語義分析，從而推斷出與自然語言意見相關的概念和情感信息，從而實現從（非結構化的）文本信息到（結構化的）可機器處理的數據的更高效轉換。