Semantic relations of Chinese verb-complement structure are complicated, which is difficult to analyze semantic relations in NLP. This paper proposes a novel model based on “the Feature Structure theory” and applies it in representing the semantic relations among the four components, which are subject, verb, object and complement. We annotated the fifteen types of semantic relations, and compar...

Semantic feature norms, originally utilized in the field of psycholinguistics as a tool for studying human semantic representation and computation, have recently attracted the attention of some NLP/IR researchers who wish to improve their task performances. However, currently available semantic feature norms are, by nature, not well-structured, making them difficult to integrate into existing r...

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...

Software project management is one of the significant activates in the software development process. Software Development Effort Estimation (SDEE) is a challenging task in the software project management. SDEE is an old activity in computer industry from 1940s and has been reviewed several times. A SDEE model is appropriate if it provides the accuracy and confidence simultaneously before softwa...

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...

This article concerns the general functional features of an adjective in modern English, and in particular multistate lexical item “just”, which carries different meanings in different variants of combinatorics. The authors analyze the combinations used with the adjectival lexeme item “just” and reveal the categories that determine the degree of semantic content of each given statement. The nee...

This paper presents the RaGoÛt system developed in response to the ECCBR’08 Computer Cooking Contest call. It proposes a case authoring approach that combines domain-specific and independent knowledge sources to create a feature vector representation of recipes. Case retrieval uses semantic similarity knowledge acquired from WordNet. This is combined with exact matching to enforce adaptation-aw...

We introduce a new approach to unsupervised estimation of feature-rich semantic role labeling models. Our model consists of two components: (1) an encoding component: a semantic role labeling model which predicts roles given a rich set of syntactic and lexical features; (2) a reconstruction component: a tensor factorization model which relies on roles to predict argument fillers. When the compo...

Finding and accessing suitable information in the open and distributed environments of current Spatial Data Infrastructures (SDIs) is a crucial task. Catalogues provide searchable repositories of information descriptions, but the mechanisms to support the tasks of discovery and retrieval are still insufficient. Problems of semantic heterogeneity caused by synonyms and homonyms can arise during ...

Semantic relatedness between words has been extracted from a variety of sources. In this ongoing work, we explore and compare several options for determining if semantic relatedness can be extracted from navigation structures in Wikipedia. In that direction, we first investigate the potential of representation learning techniques such as DeepWalk in comparison to previously applied methods base...