TMNZ 2016 : First New Zealand Text Mining Workshop
Call For Papers
MOTIVATION AND OBJECTIVES
In recent times, there has been an astronomical surge in demand for data scientists with Harvard Business Review naming Data Scientist as “The Sexiest Job of the 21st Century”.
The workshop will aim to foster collaboration among Data Science academics and practitioners focusing on text data. We have reached a point in Data Science where there is an increasing demand to integrate information from text data into models. This workshop calls for recent advances made both in the area of theoretical Text Processing dealing with lower level algorithms as well applications in Text Mining. The workshop aims to foster collaboration between academic researchers and practitioners so that the two groups could be able to integrate new advances in approaches into real world innovations being worked on by the practitioners.
TOPICS OF INTEREST
Papers are solicited from the following list of topics, however papers dealing with any aspect of Natural Language Processing, Text Processing and Text Mining are welcome.
- Topic detection/Modelling
- Sentiment detection
- Language modelling
- Social Media text processing
- Information Extraction
- Knowledge based Predictive models
- Knowledge Representation
- Linked Data Development/Applications
- Parsing, NER, POS tagging
- Pragmatics Discourse Semantics
- Lexicon Development
- Natural Language Generation
Paper submission and reviewing for this workshop will be electronic via EasyChair (https://easychair.org/conferences/?conf=tmnz2016). The papers should be written in English, following the Springer LNCS format, and be submitted in PDF on or before Sept. 30, 2016.
The following types of contributions are welcome. The recommended page length is given in brackets. There is no strict page limit but the length of a paper should be commensurate with its contribution.
Full research papers (8-12 pages);
Short research papers (4-6 pages);
System papers (4-6 pages).
Accepted papers will be posted on this website and published as a volume in the CEUR Workshop Proceedings series. In addition, selected papers will be invited to submit their extended version for a special issue in MDPI Information journal.
At least one author from each accepted paper must register for the workshop. Please see the ACML 2016 website (http://www.acml-conf.org/2016/) for information about accommodation and registration.
Parma Nand, Auckland University of Technology, New Zealand
Rivindu Perera, Auckland University of Technology, New Zealand
Yun Sing Koh, University of Auckland, New Zealand
Waseem Ahmad, Waiariki Institute of Technology, New Zealand
Krishna Raghuwaiya, The University of the South Pacific, Fiji
Muhammad Asif Naeem, Auckland University of Technology, New Zealand
Gisela Klette, Auckland University of Technology, New Zealand
Sarah Marshall, Auckland University of Technology, New Zealand