Call for Papers
The workshop aims at bringing together researchers with diverse interdisciplinary backgrounds interested in mining, managing and searching scholarly big data using new AI technologies or analyzing their transferability from one domain to another. The topics of interest include, but are not limited to:
- New AI approaches to measuring the impact of research funding and publications as well as the impact of researchers in a particular field of study:
- Identifying influential authors, experts, and collaborators within or across disciplines.
- Modeling the referencing behavior across disciplines.
- Automatic citation recommendation.
- Mining large digital libraries of scientific publications and linking to other databases such as funded proposals and patents:
- Identifying research trends and topics.
- Extracting relevant information from research articles, including an asrticle's metadata and keyphrase extraction.
- Scaling up machine learning algorithms to large research and related datasets.
- Classification and clustering of scientific trends, publications, funded proposal, patents, etc.
- Large scale linking of various entities, e.g., articles with articles by similarity, articles with their corresponding presentation slides, articles with the corresponding funded proposals.
- Presenting open-access, novel datasets (e.g., based on Wikipedia, DBpedia, United States Census Bureau data, Patent data, etc.) that can be linked to entities, and can help researcher develop novel technologies for analyzing scientific publications.
- Effectively indexing and searching large scale academic documents and other resources.