Together with Patrice Bellot (Advisory Editor) and Sébastien Fournier (Guest Editor), I am Guest Editor for a topical issue of Open Computer Science journal entitled “Topical Issue on Intelligent Methods for Textual Information Retrieval”. It is with great pleasure that I contribute to this open science publication.
De Gruyter link for the issue:
April 30th, 2019.
Machine learning approaches for intelligent text mining and retrieval are actively studied by researchers in natural language processing, information retrieval and other related fields. While supervised methods usually attain much better performance than unsupervised methods, they also require annotated data which is not always available or easy to obtain. Hence, we encourage the submission of supervised, unsupervised or hybrid methods for intelligent text retrieval tasks. Methods studying alternative learning paradigms, e.g. semi-supervised learning, weakly-supervised learning, zero-shot learning, but also transfer learning, are very welcome as well.
This thematic special issue covers three research areas: natural language processing, computational linguistics and information retrieval. The submissions may address, but are not limited to, the following topics:
- information retrieval
- information extraction
- query processing
- word sense disambiguation/discrimination
- machine learning in NLP
- sentiment analysis and opinion mining
- contradiction and controversy detection
- social media
- text mining
- text categorization and clustering
The submitted papers will undergo peer review process before they can be accepted. Notification of acceptance will be communicated as we progress with the review process.