The Smart Book Recommender(SBR) is a semantic application designed to support the Springer Nature editorial team in promoting their publications at Computer Science venues. It takes as input the proceedings of a conference and suggests books, journals, and other conference proceedings that are likely to be relevant to the attendees of the conference in question. It does so by taking advantage of a semantic representation of topics, which builds on a very large ontology of Computer Science topics; characterizing Springer Nature books as distributions of semantic topics; and approaching the problem as one of semantic matching between such distributions of semantic topics.
Snapshot of the main interface of the Smart Book Recommender
SBR stems from the ongoing collaboration between Springer Nature and the Knowledge Media Institute (KMi) of the Open University, which has produced a number of other innovative solutions, including Smart Topic Miner (STM), a semantic framework for classifying academic documents, and its API, the Smart Topic API. Since January 2017, STM is being routinely used by the SN Computer Science editorial team, halving the time for classifying conference proceedings. Similarly, SBR is in line to be adopted to support SN editors in selecting the best set of books to market to the participants of a conference.
"Smart Book Recommender: A Semantic Recommendation Engine for Editorial Products" is a poster paper that will be presented at the International Semantic Web Conference (ISWC) 2017, 21-25 October 2017, Vienna, Austria. Authors Francesco Osborne, Thiviyan Thanapalasingam, Angelo Salatino, Aliaksandr Birukou and Enrico Motta Abstract Academic publishers, such as Springer Nature, need to constantly make informed decisions about how and where to market their editorial products. In…
"Smart Topic Miner: Supporting Springer Nature Editors with Semantic Web Technologies" is poster paper presented at the Poster and Demo session [D45] on Wednesday 19th October 2016 at the 15th International Semantic Web Conference in Kobe, Japan Authors: Francesco Osborne, Angelo Antonio Salatino, Aliaksandr Birukou and Enrico Motta Abstract: Academic publishers, such as Springer Nature, annotate scholarly products with the appropriate research topics and keywords to facilitate the…
Smart Topic Miner (STM) is a web application which uses Semantic Web technologies to classify scholarly publications on the basis of Computer Science Ontology (CSO), a very large automatically generated ontology of research areas. STM was developed to support the Springer Nature Computer Science editorial team in classifying proceedings in the LNCS family. It analyses in real time a set of publications provided by…
