In recent years, interest in heterogeneous information network analysis (HINA) have led to advances in information propagation models, community detection, analysis of citation and collaboration networks, and recommender systems. Three previous workshops on HINA have focused on the convergence of methodologies for network modeling, incorporating representation of heterogeneity (especially author-item-author and author-item-venue-item-author networks), path analysis, frequent subgraph mining, and using learning and inference in graphical models of probability to capture important aspects of heterogeneous information networks.
Active research areas that are relevant to heterogeneous information networks include:

• Models of information propagation across domains and social media
• Progressing beyond APA and APVPA models of citation networks
• Social sentiment analysis and topic models in HINA
• Community detection and formation modeling
• Path-based similarity measures and relationship extraction
• Applications to modeling of weblogs, social media, social networks, and the semantic web
• Trust networks, information sharing, and limitations of existing models
• Learning to rank in HINA
• Modeling of link types and relationship strength

(The first three of these are new topics not addressed in any previous HINA workshops.)

The emphasis of this workshop shall be approaches based on relationship extraction from heterogeneous sources including but not limited to: social media, social news, collaboration networks, and document collections.


IMPORTANT DATES:

Monday, May 09, 2016 (extended from April 18) - Abstract registration (optional)
Friday, May 06, 2016 (extended from April 22) - Full papers due
Friday, May 13, 2016 (extended from April 29) - Short papers due
Friday, May 20, 2016 - Acceptance notification
Monday, May 30, 2016 - Camera ready copy due
Saturday, July 9, 2016 - Monday, July 11, 2016 HINA workshop (half-day; exact date TBD)