Topics in semantic representation.

Query expansion based on relevance feedback and latent semantic analysis

Web search engines are one of the most popular tools on the Internet which are widely-used by expert and novice users. Constructing an adequate query which represents the best specification of users’ information need to the search engine is an important concern of web users. Query expansion is a way to reduce this concern and increase user satisfaction. In this paper, a new method of query expa...

A Joint Semantic Vector Representation Model for Text Clustering and Classification

Text clustering and classification are two main tasks of text mining. Feature selection plays the key role in the quality of the clustering and classification results. Although word-based features such as term frequency-inverse document frequency (TF-IDF) vectors have been widely used in different applications, their shortcoming in capturing semantic concepts of text motivated researches to use...

Situation and Text: Representation of Migrants Whilst the Escalation of Refugee Crisis in Great Britain as Compared to Russia

Increasing migration is a vital concern for a globalizing sociocultural environment in today’s world. The UK and developed European countries have become an attractive destination for asylum seekers (labelled as “migrants”) in the past decade. The rapid rise in the number of asylum seekers, which was labelled “migration crisis” (Ruz, 2015), made this topic an integral part of scientific discuss...

The Effect of Semantic Transfer on Iranian EFL Learners’ Lexical Representation and Processing

Multi-Resolution Modelling Of Topic Relationships In Semantic Space

Recent techniques for document modelling provide means for transforming document representation in high dimensional word space to low dimensional semantic space. The representation with coarse resolution is often regarded as being able to capture intrinsic semantic structure of the original documents. Probabilistic topic models for document modelling attempt to search for richer representations...

The Topics they are a-Changing - Characterising Topics with Time-Stamped Semantic Graphs

DBpedia has become one of the major sources of structured knowledge extracted from Wikipedia. Such structures gradually re-shape the representation of Topics as new events relevant to such topics emerge. Such changes make evident the continuous evolution of topic representations and introduce new challenges to supervised topic classification tasks, since labelled data can rapidly become outdate...