Book ChapterDOI
Applying Semantic Relations for Automatic Topic Ontology Construction
Subramaniyaswamy Vairavasundaram,R. Logesh +1 more
- pp 48-77
TLDR
An automatic topic ontology construction process for better topic classification is developed and a corpus based novel approach to enrich the set of categories in the ODP by automatically identifying concepts and their associated semantic relationships based on external knowledge from Wikipedia and WordNet is presented.Abstract:
The rapid growth of web technologies had created a huge amount of information that is available as web resources on Internet. Authors develop an automatic topic ontology construction process for better topic classification and present a corpus based novel approach to enrich the set of categories in the ODP by automatically identifying concepts and their associated semantic relationships based on external knowledge from Wikipedia and WordNet. The topic ontology construction process relies on concept acquisition and semantic relation extraction. Initially, a topic mapping algorithm is developed to acquire the concepts from Wikipedia based on semantic relations. A semantic similarity clustering algorithm is used to compute similarity to group the set of similar concepts. The semantic relation extraction algorithm derives associated semantic relations between the set of extracted topics from the lexical patterns in WordNet. The performance of the proposed topic ontology is evaluated for the classification of web documents and obtained results depict the improved performance over ODP.read more
Citations
More filters
Journal ArticleDOI
Fog computing-based intelligent healthcare system for the detection and prevention of mosquito-borne diseases
TL;DR: The experimental evaluation reveals the improved performance of the proposed F-HMRAS with 95.9% classification accuracy, and the fuzzy k-nearest neighbor approach is employed to categorize the user into infected or uninfected class.
Journal ArticleDOI
Intelligent cyber-physical system for an efficient detection of Parkinson disease using fog computing
Malathi Devarajan,Logesh Ravi +1 more
TL;DR: An intelligent system for detecting Parkinson’s disease to provide proper medication by analysing voice samples using Fog computing as a midway layer between end devices and the cloud server is proposed.
Journal ArticleDOI
Named entity recognition for extracting concept in ontology building on Indonesian language using end-to-end bidirectional long short term memory
Joan Santoso,Esther Irawati Setiawan,Christian Nathaniel Purwanto,Eko Mulyanto Yuniarno,Mochamad Hariadi,Mauridhi Hery Purnomo +5 more
TL;DR: The main focus in this research is to extract concepts in Ontology Building automatically using Named Entity Recognition, an end-to-end model using Bidirectional Long Short Term Memory (Bi-LSTM) that is able to perform a sequence classification task by understanding the context of the input.
Journal ArticleDOI
Location-based personalized recommender system in the internet of cultural things
Journal Article
Neighborhood-based approach of collaborative filtering techniques for book recommendation system
TL;DR: The expected outcome has been achieved through collaborative filtering with the help of correlation techniques which in turn comprises of Pearson correlation, cosine similarity, Kendall’ s Tau correlation, Jaccard similarity, Spearman Rank Correlation, Mean-squared distance, etc.
References
More filters
Book
Modern Information Retrieval
TL;DR: In this article, the authors present a rigorous and complete textbook for a first course on information retrieval from the computer science (as opposed to a user-centred) perspective, which provides an up-to-date student oriented treatment of the subject.
Book ChapterDOI
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
TL;DR: This paper explores the use of Support Vector Machines for learning text classifiers from examples and analyzes the particular properties of learning with text data and identifies why SVMs are appropriate for this task.
Journal ArticleDOI
Introduction to WordNet: An On-line Lexical Database
TL;DR: Standard alphabetical procedures for organizing lexical information put together words that are spelled alike and scatter words with similar or related meanings haphazardly through the list.
Ontology Development 101: A Guide to Creating Your First Ontology
TL;DR: An ontology defines a common vocabulary for researchers who need to share information in a domain that includes machine-interpretable definitions of basic concepts in the domain and relations among them.
Proceedings ArticleDOI
Yago: a core of semantic knowledge
TL;DR: YAGO as discussed by the authors is a light-weight and extensible ontology with high coverage and quality, which includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE).