Sentiment Progression Based Searching and Indexing of Literary Textual Artefacts

Literary artefacts are generally indexed and searched based on titles, meta data and keywords over the years. This searching and indexing works well when user/reader already knows about that particular creative textual artefact or document. This indexing and search hardly takes into account interest and emotional makeup of readers and its mapping to books. In case of literary artefacts, progression of emotions across the key events could prove to be the key for indexing and searching. In this paper, we establish clusters among literary artefacts based on computational relationships among sentiment progressions using intelligent text analysis. We have created a database of 1076 English titles + 20 Marathi titles and also used database http://​www.​cs.​cmu.​edu/​~dbamman/​booksummaries.​html with 16559 titles and their summaries. We have proposed Sentiment Progression based Search and Indexing (SPbSI) for locating and recommending books. This can be used to create personalized clusters of book titles of interest to readers. The analysis clearly suggests better searching and indexing when we are targeting book lovers looking for a particular type of books or creative artefacts.