Abstract
With the rapid development of social computing technologies and online reading platforms, the proportion of e-books, especially online serialized novels, has been increasing. Identifying ways to add updated serialized books to readers’ real-time recommendation lists has become an urgent problem to be solved. While serialized books are still underwritten and in the process of production, their features and categories can constantly evolve and change, lacking complete text content information and complete global scoring data. Therefore, this paper proposes a dynamic DTree2Vec scheme for serialized books that models text of varying degrees of completion to achieve unified semantic feature representation to measure the semantic relevance of books. At the same time, it ensures recommendation quality by tracking the update status of serialized books and by adding the subsequent chapter content in real time. This scheme establishes a dynamic hierarchical tree structure for serialized books and applies a cosine-type local reconstruction model to reconstruct new semantic features of books. In addition, the fine-grained factor of chapter partitioning is introduced to the reconstruction process to adjust the proportion of global and local features to better represent the semantic features of books. We analyzed effects of the content of serialized chapters on the recommendation results and used semantic features of the reconstruction to represent the content of serial novels in real time. The experiment results prove that the proposed DTree2Vec scheme can achieve higher degrees of recommendation accuracy when dealing with unfinished serialized books, effectively alleviating dynamic capture problems and real-time recommendations of book recommendations.
Highlights
With the rapid development of social computing technologies and with the popularization of electronic reading devices and online reading platforms, e-books have become popular due to their low cost and portability
Major online platforms and e-book reading websites have introduced and promoted a large proportion of serialized novels. These serialized books are updated in real time for readers to meet their diverse needs for reading content
Serialized books often take a long time to produce while calling for loyal readers, and the matching of readers with unfinished books has become an urgent problem
Summary
With the rapid development of social computing technologies and with the popularization of electronic reading devices and online reading platforms, e-books have become popular due to their low cost and portability. Major online platforms and e-book reading websites have introduced and promoted a large proportion of serialized novels These serialized books are updated in real time for readers to meet their diverse needs for reading content. H. Zhao et al.: Dtree2vec: High-Accuracy and Dynamic Scheme for Real-Time Book Recommendation changes in the story content of updated serialized books and the application of such changes to readers’ real-time recommendation lists have become urgent problems to be solved. Because the classified information of serial novels often changes with the development of story content through the process of production, it is clearly not accurate enough to strictly make recommendations according to original labels. The dynamic DTree2Vec scheme is proposed in this paper This scheme models text of varying degrees of completion to exhibit unified semantic feature representation and to measure the semantic relevance of books.
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