Natural Language Processing and Event Extraction for Big Data

Dear Colleagues,

The amount of textual data shared on the Web is overwhelming, and specific techniques are required to manage it and gather knowledge. Event Extraction (EE) is a sub-task of Information Retrieval (IR) whose scope is to extract events automatically from the text, understand what is happening around the world and identify information about where and when it happened and who was involved.

EE has received considerable attention and has seen great progress in recent years. Several approaches have been developed distinguishing two types of EE: Sentence-level Event Extraction and Document-level Event Extraction. Hence, Natural Language Processing (NLP) techniques play a key role in this challenge allowing the extraction of structured information from freeform text. However, the works currently in the literature are not mature enough to allow for the identification of a definitive approach to the challenge of EE, each study addresses only a part of the problem and very often the proposed methodologies are language specific. The research field of EE is still open to different margins for improvement.

The scope of this Special Issue is to collect recent advances in NLP in the field of EE, focusing on techniques that are able to process text published on the Web, e.g., social media and online newspapers, and identify event descriptions (participants, location, and time).

The areas of interest of this Special Issue include (but are not limited to):

• Sentence-level Event Extraction;
• Document-level Event Extraction;
• Question answering;
• Named entity recognition and linking;
• Semantic technologies;
• Text categorization;
• Natural Language Understanding;
• Temporal annotation;
• Knowledge graph;
• Graph analysis;
• Event deduplication;
• Text similarity.

Dr. Federica Rollo
Dr. John Blake
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.