Heterogeneous Information Network Analysis (HINA) A Workshop of the 26th International Joint Conference on Artificial Intelligence (IJCAI-2017) Melbourne, Australia | August 19-25, 2017 (Afternoon Workshop)
(Dates and other information to be updated soon. Check back next week!)
Workshop Overview

5th IJCAI Workshop on Heterogeneous Information Network Analysis (HINA-2017)

Recent work on heterogeneous information networks (HIN) has led to a convergence of methodologies for network modeling, incorporating classification, learning and reasoning with graphical models, frequent subgraph mining, relational representation, and link annotation, among other techniques. Many intelligent systems applications to information extraction, web search, and recommendation call for inferences to be made regarding the existence, type, or attributes of links. Some tasks, such as question answering using information networks, may require that inferences be based upon partial link information and made under uncertainty about participating entities and relationships.

Active research areas that are relevant to heterogeneous information networks include:

The emphasis of this workshop shall be approaches based on relationship extraction from heterogeneous sources such as technical literature, news articles, social network profile data, and social media. Relevant media include, but are not limited to, forums, blogs, social media systems such as Facebook, Twitter, YouTube, Google+, Pinterest, Tumblr, etc. Of particular interest are sharing mechanisms, status updates, systems for rating and commenting, and embedded content in the deep web, including images and video. However, the scope is not limited to any particular approach to link analysis or any source of network information such as text corpora. Application areas that often exhibit a need for heterogeneous information network analysis include:

This workshop shall help to bring together people from these different areas and present an opportunity for researchers and practitioners to share new techniques for identifying and analyzing relationships in networks that integrate multiple types or sources of information.

Call for papers Published papers