Automatic Topic Ontology Construction Using Semantic Relations from WordNet and Wikipedia

2013 ◽  
Vol 9 (3) ◽  
pp. 61-89 ◽  
Author(s):  
V. Subramaniyaswamy
Keyword(s):  
Web Mining ◽  
Relation Extraction ◽  
Past Research ◽  
Semantic Relations ◽  
Svm Classifier ◽  
Ontology Construction ◽  
Knowledge Resources ◽  
Web Resources ◽  
The Past ◽  
The Web

Due to the explosive growth of web technology, a huge amount of information is available as web resources over the Internet. Therefore, in order to access the relevant content from the web resources effectively, considerable attention is paid on the semantic web for efficient knowledge sharing and interoperability. Topic ontology is a hierarchy of a set of topics that are interconnected using semantic relations, which is being increasingly used in the web mining techniques. Reviews of the past research reveal that semiautomatic ontology is not capable of handling high usage. This shortcoming prompted the authors to develop an automatic topic ontology construction process. However, in the past many attempts have been made by other researchers to utilize the automatic construction of ontology, which turned out to be challenging due to time, cost and maintenance. In this paper, the authors have proposed a corpus based novel approach to enrich the set of categories in the ODP by automatically identifying the concepts and their associated semantic relationship with corpus based external knowledge resources, such as Wikipedia and WordNet. This topic ontology construction approach relies on concept acquisition and semantic relation extraction. A Jena API framework has been developed to organize the set of extracted semantic concepts, while Protégé provides the platform to visualize the automatically constructed topic ontology. To evaluate the performance, web documents were classified using SVM classifier based on ODP and topic ontology. The topic ontology based classification produced better accuracy than ODP.

Applying Semantic Relations for Automatic Topic Ontology Construction

2018 ◽  
pp. 48-77 ◽  
Author(s):  
Subramaniyaswamy Vairavasundaram ◽  
Logesh R.
Keyword(s):  
Clustering Algorithm ◽  
Relation Extraction ◽  
Semantic Relation ◽  
Semantic Relations ◽  
Construction Process ◽  
Ontology Construction ◽  
Web Documents ◽  
Mapping Algorithm ◽  
Novel Approach ◽  
Improved Performance

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.

Towards Large-Scale Unsupervised Relation Extraction from the Web

2012 ◽  
Vol 8 (3) ◽  
pp. 1-23 ◽  
Author(s):  
Bonan Min ◽  
Shuming Shi ◽  
Ralph Grishman ◽  
Chin-Yew Lin
Keyword(s):  
Information Extraction ◽  
Large Scale ◽  
Relation Extraction ◽  
Previous Method ◽  
Semantic Relations ◽  
Large Set ◽  
Semantic Classes ◽  
Extraction Algorithm ◽  
Unsupervised Algorithms ◽  
The Web

The Web brings an open-ended set of semantic relations. Discovering the significant types is very challenging. Unsupervised algorithms have been developed to extract relations from a corpus without knowing the relation types in advance, but most rely on tagging arguments of predefined types. One recently reported system is able to jointly extract relations and their argument semantic classes, taking a set of relation instances extracted by an open IE (Information Extraction) algorithm as input. However, it cannot handle polysemy of relation phrases and fails to group many similar (“synonymous”) relation instances because of the sparseness of features. In this paper, the authors present a novel unsupervised algorithm that provides a more general treatment of the polysemy and synonymy problems. The algorithm incorporates various knowledge sources which they will show to be very effective for unsupervised relation extraction. Moreover, it explicitly disambiguates polysemous relation phrases and groups synonymous ones. While maintaining approximately the same precision, the algorithm achieves significant improvement on recall compared to the previous method. It is also very efficient. Experiments on a real-world dataset show that it can handle 14.7 million relation instances and extract a very large set of relations from the Web.

scholarly journals WEB MINING НА ОСНОВІ ЛЯМБДА АРХІТЕКТУРИ

World Science ◽  
2018 ◽  
Vol 2 (7(35)) ◽  
pp. 4-8
Author(s):  
Фінчук О. В.
Keyword(s):  
Web Mining ◽  
Huge Amount ◽  
Web Resources ◽  
Lambda Architecture ◽  
The World ◽  
Normal Human ◽  
The Web

Amount of data in the web is growing rapidly from day to day and for normal human it's hard to realize what is actually happening in the world at the current moment, so it is required to have a system which allows collect and analyze huge amount of variety data from different web resources. The system should be able to process a lot of data fast and be capable to store all collected data for future processing. How to achieve this with use of lambda architecture is described in this article.

scholarly journals Requisite for Web Usage Mining – A Survey

2013 ◽  
pp. 67-73
Author(s):  
Sindhu P Menon ◽  
Nagaratna P Hegde
Keyword(s):  
Web Sites ◽  
Web Mining ◽  
World Wide ◽  
Research Area ◽  
Important Research ◽  
The Past ◽  
The World ◽  
Important Research Area ◽  
Indispensable Tool ◽  
The Web

The World Wide Web (Web) has been providing an important and indispensable platform for receiving information and disseminating information as well as interacting with society on the Internet. With its astronomical growth over the past decade, the Web becomes huge, diverse and dynamic. The application of data mining techniques to the web is called Web Mining. Web Mining aims to discover interesting patterns in the structure, the contents and the usage of web sites. An indispensable tool for the webmaster, it has, nevertheless, a long road ahead in which visualisation plays an important role. Currently, Web mining techniques has emerged as an important research area to help Web users find the information needed. This paper is an effort in analysing the views and methodologies stated by various authors on various processes in mining the web.

Research on Ranking Algorithms in Web Structure Mining

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Suvarna Sharma ◽  
Amit Bhagat
Keyword(s):  
Web Mining ◽  
Review Paper ◽  
Search Algorithm ◽  
Web Pages ◽  
Page Rank ◽  
The Past ◽  
Ranking Algorithms ◽  
Web Structure ◽  
Web Structure Mining ◽  
The Web

In the past few decades, the Web has emerged as a treasure of information and web mining is a technique to handle this treasure. During recent years web mining has been a well-researched area. Web mining is the application of the data mining which is useful to extract the knowledge from web. With the progress of web, more and more data are now available for users on web. Web structure mining deals with the contents and hyperlinks on web pages. In this review paper, we have focused on three basic algorithms for evaluating the importance of pages i.e. Page Rank, Weighted Page Rank, and Hyperlink-Induced Topic Search and comparison of those algorithms. Page Rank algorithm is based on back links of the page and it calculates the rank of web pages at indexing time. Weighted Page Rank algorithm scores pages according to their relevancies and rank of a page is calculated by its number of incoming and outgoing links. Hyperlink-induced topic search algorithm is an iterative algorithm developed to quantify each pages value as an authority and as a hub. This study was done basically to explore the link structure algorithms for ranking pages.

Exploring the Boundaries of the Number–Temporal Order Association

2015 ◽  
Vol 62 (3) ◽  
pp. 198-205 ◽  
Author(s):  
Dana Ganor-Stern
Keyword(s):  
Embodied Cognition ◽  
Mental Representation ◽  
Temporal Order ◽  
Past Research ◽  
Numerical Comparison ◽  
Negative Number ◽  
Comparison Task ◽  
Negative Numbers ◽  
The Past

Past research has shown that numbers are associated with order in time such that performance in a numerical comparison task is enhanced when number pairs appear in ascending order, when the larger number follows the smaller one. This was found in the past for the integers 1–9 ( Ben-Meir, Ganor-Stern, & Tzelgov, 2013 ; Müller & Schwarz, 2008 ). In the present study we explored whether the advantage for processing numbers in ascending order exists also for fractions and negative numbers. The results demonstrate this advantage for fraction pairs and for integer-fraction pairs. However, the opposite advantage for descending order was found for negative numbers and for positive-negative number pairs. These findings are interpreted in the context of embodied cognition approaches and current theories on the mental representation of fractions and negative numbers.

scholarly journals Ecodesign—A Review of Reviews

2020 ◽  
Vol 13 (1) ◽  
pp. 315
Author(s):  
Malte Schäfer ◽  
Manuel Löwer
Keyword(s):  
Success Factors ◽  
Research Question ◽  
Pollution Prevention ◽  
Past Research ◽  
The Past ◽  
Review Articles ◽  
Complete Life Cycle ◽  
Review Of Reviews ◽  
Research Questions ◽  
Over Time

With the intent of summing up the past research on ecodesign and making it more accessible, we gather findings from 106 existing review articles in this field. Five research questions on terminology, evolution, barriers and success factors, methods and tools, and synergies, guide the clustering of the resulting 608 statements extracted from the reference. The quantitative analysis reveals that the number of review articles has been increasing over time. Furthermore, most statements originate from Europe, are published in journals, and address barriers and success factors. For the qualitative analysis, the findings are grouped according to the research question they address. We find that several names for similar concepts exist, with ecodesign being the most popular one. It has evolved from “end-of-pipe” pollution prevention to a more systemic concept, and addresses the complete life cycle. Barriers and success factors extend beyond the product development team to management, customers, policymakers, and educators. The number of ecodesign methods and tools available to address them is large, and more reviewing, testing, validation, and categorization of the existing ones is necessary. Synergies between ecodesign and other research disciplines exist in theory, but require implementation and testing in practice.

scholarly journals Water accounting for water management at the river basin scale in India: approaches and gaps

Water Policy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 768-788
Author(s):  
Nitin Bassi ◽  
Guido Schmidt ◽  
Lucia De Stefano
Keyword(s):  
Water Management ◽  
River Basin ◽  
Water Policy ◽  
Past Research ◽  
River Basin Scale ◽  
The Past ◽  
Basin Scale ◽  
Water Accounting ◽  
Accounting Approaches ◽  
National Water

Abstract The main objective of this research paper is to assess the extent to which the concept of water accounting has been applied for water management at the river basin scale in India. For this, the study first assesses the importance given to the use of water accounting for water management in India's national water policy. It then analyses the evolution of water accounting approaches in India through a systematic review of the past research studies on the theme. Further, it looks at their contribution to decision-making concerning allocation of water resources and resolving conflicts over water sharing. Finally, it identifies the existing gaps in the methodologies for water accounting so far used in India.

scholarly journals Chasing the green buck? Environmental activism in post-communist Baltic States

2016 ◽  
Vol 49 (3) ◽  
pp. 243-254 ◽  
Author(s):  
Timofey Agarin ◽  
Miķelis Grīviņš
Keyword(s):  
Political Process ◽  
Past Research ◽  
The Political ◽  
Economic Interests ◽  
Economic Resource ◽  
International Networks ◽  
The Core ◽  
The Past ◽  
National Environment ◽  
Collapse Of Communism

The paper investigates the dynamics and volution of issues on the agenda of Baltic environmental non-governmental organisations (NGOs) since the collapse of communism. The past research on Baltic environment activism suggests that these enjoy high visibility because they tapped the core societal views of natural environment as a crucial asset of a nation. As we demonstrate in this paper, the changes in agendas of Baltic environmental non-governmental organisations (ENGOs) make clear that the rhetorical toolbox of ‘national environment’ is often used to mainly achieve greater financial gains for individual members, rather than for society at large. We illustrate how the dearth of economic opportunities for domestic public has impacted perceptions of ‘nature’ advocated by the environmental activists, focussing specifically on national perceptions of ownership and the resulting actions appropriating ‘nature’ as a source for economic development, only tangentially attaining environmental outcomes on the way. The vision that the ‘environment’ is an economic resource allowed ENGO activists to cooperate with the domestic policymaking, while tapping international networks and donors for funding. Throughout the past decades they worked to secure their own and their members’ particularistic economic interests and, as we demonstrate, remained disengaged from the political process and failed to develop broader reproach with publics.

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