HINA 2015 - 3rd Workshop on Heterogeneous Information Network Analysis (HINA)

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:
Community detection and formation modeling
Ranking-based clustering methods: learning to rank in information networks
Path-based similarity measures and relationship extraction
Modeling of link types and relationship strength
Applications to modeling of weblogs, social media, social networks, and the semantic web
Frequent pattern mining in graph and sequence data
Statistical relational learning
Trust networks and information sharing
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:
Information diffusion and sharing systems: sensor networks, social media (opinions and sentiments, meme propagation, viral content, political commentary, etc.)
Behavioral modeling: community recruitment and mass activity, large-scale patterns, traffic, spatiotemporal effects
Content-management systems: version control, wikification
Social recommender systems: communities, experts, friends, products, reviewers, providers
Application areas: cybersecurity (information flow, trust networks, attack graphs, mechanism design), bioinformatics and biomedicine (genomics, proteomics, metabolomics), epidemiology
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.