Automated topic labelling brings benefits for users aiming at analysing and understanding
document collections, as well as for search engines targetting at the linkage between groups …

Semantic relatedness and disambiguation are fundamental problems for linking text
documents to the Web of Data. There are many approaches dealing with both problems but …

Entity Linking (EL) consists of determinating the entities that best represent the mentions in a
document. Mentions can be very ambiguous and can refer to different entities in different …

Hierarchical Topic Modeling is the probabilistic approach for discovering latent topics
distributed hierarchically among the documents. The distributed topics are represented with …

Text mining is a new branch of AI that employs natural language processing techniques to
convert unstructured text into a structured format for easier comprehension. It is becoming …

Since its inception in the last decade, the Semantic Web has experienced a steady and
continuous development toward its original vision, both in terms of research and of …

Word sense disambiguation is a process to correctly identify the meanings of words in a
given context. Being important in many natural language processing applications, this …

Set intersection counting appears as a subroutine in many techniques used in natural
language processing, in which similarity is often measured as a function of document …

[目的] 对面向主题模型的主题自动语义标注方法进行总结与评述, 以促进主题模型的发展与应用.
[文献范围] 在Web of Science 和CNKI 数据库中分别以“Topic Labeling OR Topic Labelling OR …

In this paper we study whether state-of-the-art techniques for multi-domain and multilingual
entity linking can be ported to the clinical domain. To do so, we compare two known entity …