Semantic Representation and Integration of Digital Evidence

An Improved Semantic Schema Matching Approach

Schema matching is a critical step in many applications, such as data warehouse loading, Online Analytical Process (OLAP), Data mining, semantic web [2] and schema integration. This task is defined for finding the semantic correspondences between elements of two schemas. Recently, schema matching has found considerable interest in both research and practice. In this paper, we present a new impr...

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

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...

An open architecture for digital evidence integration

Recently the need for “digital evidence bags” – a common storage format for digital evidence – has been identified as a key requirement for enabling inter-organisational sharing of digital evidence, and interoperability between forensic analysis tools. Recent work has described an ontology based approach to correlation of event log based evidence, using semantic web technologies for describing ...

Developing a BIM-based Spatial Ontology for Semantic Querying of 3D Property Information

With the growing dominance of complex and multi-level urban structures, current cadastral systems, which are often developed based on 2D representations, are not capable of providing unambiguous spatial information about urban properties. Therefore, the concept of 3D cadastre is proposed to support 3D digital representation of land and properties and facilitate the communication of legal owners...