Text Analytics using semantic information is the latest trend of research due to its potential to represent better the texts content compared with the bag-of-words approaches. On the contrary, representation of semantics through graphs has several advantages over the traditional representation of feature vector. Therefore, error tolerant graph matching techniques can be used for text comparison...

A new framework based on multimodal semantic clues and HCRF (Hidden Conditional Random Field) for soccer wonderful event detection. Through analysis of the structural semantics of the wonderful event videos, define nine kinds of multimodal semantic clues to accurately describe the included semantic information of the wonderful events. After splitting the video clips into several physical shots,...

Lexical attributes, like syntactic (part-of-speech) and semantic (semantic category) attributes, are in most cases, ambiguous in every languages. Automatic resolution of ambiguity of these attributes can be achieved using different techniques; rule-based, statistical, NN-based and their hybrids. Moreover, one linguistic feature also has influence over the resolution of ambiguity of another feat...

multi-word lexical units are a typical feature of specialized dictionaries, in particular monolingual and bilingual maritime dictionaries. the paper studies the concept of the multi-word lexical unit and considers the similarities and differences of their selection and presentation in monolingual and bilingual maritime dictionaries. the work analyses such issues as the classification of multi-w...

We discuss Feature Latent Semantic Analysis (FLSA), an extension to Latent Semantic Analysis (LSA). LSA is a statistical method that is ordinarily trained on words only; FLSA adds to LSA the richness of the many other linguistic features that a corpus may be labeled with. We applied FLSA to dialogue act classification with excellent results. We report results on three corpora: CallHome Spanish,...

To make real Web information more machine processable, this paper presents a new approach to intra-page and inter-page semantic analysis of Web pages. Our approach consists of Web pages structure analysis and semantic clustering for intra-page semantic analysis, and machine learning based link semantic analysis for inter-page analysis. Based on the automatic repetitive patterns discovery in str...

Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We...

Multiple emotions are often triggered in readers in response to text stimuli like news article. In this paper, we present a novel method for classifying news sentences into multiple emotion categories using an ensemble based multi-label classification technique called RAKEL. The emotion data consists of 1305 news sentences and the emotion classes considered are disgust, fear, happiness and sadn...