The problem of joint modeling the text and image components of multimedia documents is
studied. The text component is represented as a sample from a hidden topic model, learned …

The problem of cross-modal retrieval from multimedia repositories is considered. This
problem addresses the design of retrieval systems that support queries across content …

Measuring lexical semantic relatedness is an important task in Natural Language
Processing (NLP). It is often a prerequisite to many complex NLP tasks. Despite an …

This survey documents representation approaches for classification across different
modalities, from purely content-based methods to techniques utilizing external sources of …

Cross media retrieval systems have received increasing interest in recent years. Due to the
semantic gap between low-level features and high-level semantic concepts of multimedia …

Abstract The Linked Hypernyms Dataset (LHD) provides entities described by Dutch,
English and German Wikipedia articles with types in the DBpedia namespace. The types are …

Human perceptions of music and image are closely related to each other, since both can
inspire similar human sensations, such as emotion, motion, and power. This paper aims to …

The aim of Named Entity Recognition (NER) is to identify references of named entities in
unstructured documents, and to classify them into pre-defined semantic categories. NER …

In this paper, we present a simple and effective topic correlation model (TCM) for cross-
modal multimedia retrieval by jointly modeling the text and image components in multimedia …

Hypernym extraction is a crucial task for semantically motivated NLP tasks such as
taxonomy and ontology learning, textual entailment or paraphrase identification. In this …