Semantic Knowledge Representation Project

Automatic Hashtag Recommendation in Social Networking and Microblogging Platforms Using a Knowledge-Intensive Content-based Approach

In social networking/microblogging environments, #tag is often used for categorizing messages and marking their key points. Also, since some social networks such as twitter apply restrictions on the number of characters in messages, #tags can serve as a useful tool for helping users express their messages. In this paper, a new knowledge-intensive content-based #tag recommendation system is intr...

Knowledge Representation and Retrieval in Design Project Memory

Knowledge sharing in general and the contextual access to knowledge in particular, still represent a key challenge in the knowledge management framework. Researchers on semantic web and human machine interface study techniques to enhance this access. For instance, in semantic web, the information retrieval is based on domain ontology. In human machine interface, keeping track of user's activity...

Neuron Mathematical Model Representation of Neural Tensor Network for RDF Knowledge Base Completion

In this paper, a state-of-the-art neuron mathematical model of neural tensor network (NTN) is proposed to RDF knowledge base completion problem. One of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. For this reason, a new representation of this network is suggested that solves this difficulty. In the representation, th...

A Structured Representation Of Word-Senses For Semantic Analysis

A framework for a structured representation of semantic knowledge (e.g. word-senses) has been defined at the IBM Scientific Center of Roma, as part of a project on Italian Text Understanding. This representation, based on the conceptual graphs formalism [SOW84], expresses deep knowledge (pragmatic) on word-senses. The knowledge base data structure is such as to provide easy access by the semant...

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