Track 1: Natural Language Processing Technology

Author identification and plagiarism detection

Document summarisation and identification

Natural language text generation from knowledge graphs and ontologies

Sentiment analysis

Opinion, personality and emotion detection in social media

Methods for Classification and Categorisation

Topic recognition and topic tracking, subject indexing

Methods and systems of automatic machine translation

Natural Language Processing for Digital Humanities

Resources for basic Natural Language Processing tasks analysis

Track 2: Information Retrieval, Mining & Data Analytics

Adversarial and cross language information retrieval

Aspects of high performance text analysis

Collaborative information filtering

Data mining、Data science、Text mining

Event and anomaly detection

Information, knowledge and taxonomy extraction

Information mining and psycholinguistic

Interactive, dynamic, contextual and personalised Information Retrieval

Query Expansion

Social and Multimedia Information Retrieval

Text analytics for the Internet of Things

Propagation and diffusion of information

Super popular content

Information Retrieval result evaluation and relevance feedback 

Track 3: Knowledge Graph, Semantic Web & Intelligent System

Automated knowledge acquisition and representation

Decentralised knowledge representation

Graph and deep-learning-based methods of NLP & IR

Knowledge graph learning, Knowledge representation, Knowledge discovery

Semantic search and exploratory search

Learning from Big Data for web-scale knowledge graphs

Lexical semantics for the Semantic Web

Intelligent Tutoring, Interactive Systems

Methods and analyses for statistical networks

Ontology generation, merging and verification methods

Ontology learning、Ontology population

Semantic similarity metrics and analogy

Similarity analysis, clustering, hierarchical clustering

Small world graphs

Use of knowledge graphs and ontologies for NLP

Visualisation of NLP and IR results