With the growing volume of publications in the Computer Science (CS) discipline, tracking
the research evolution and predicting the future research trending topics are of great …

Literature search is critical for any scientific research. Different from Web or general domain
search, a large portion of queries in scientific literature search are entity-set queries, that is …

Finding the lineage of a research topic is crucial for understanding the prior state of the art
and advancing scientific displacement. The deluge of scholarly articles makes it difficult to …

The rapid growth in the number of scholarly documents on the Web and in other digital
platforms makes it challenging for researchers to find research publications most relevant to …

Text-rich heterogeneous information networks (text-rich HINs) are ubiquitous in real-world
applications. Hypernymy, also known as is-a relation or subclass-of relation, lays in the core …

Purpose Full text of a document is a rich source of information that can be used to provide
meaningful topics. The purpose of this paper is to demonstrate how to use citation context …

This paper presents the results of a method for the visualization of the long-term prediction of
research trending topics. Meaningful topics were identified among the words included in the …

The Internet has been identified in human enhancement scholarship as a powerful cognitive
enhancement technology. Using the Internet as an external memory system has overall …

Entity similarity measuring is the basic work of academic search and recommendation. To
analyze and measure the similarity among entities, existing methods are mainly based on …

This paper studies a link-text algorithm to model scientific documents by citation influences,
which is applied to document clustering and influence prediction. Most existing link-text …