Enhancing Content Search Using The Semantic Web

Published Date: 02 Nov 2017

The Semantic Web is inspired by a vision of the current Web which has been in the background since its inception, and which is influenced by earlier work dating back to Vannevar Bush’s idea of the 'memex' machine in the 1940s. Tim Berners-Lee originally envisioned the WWW as including richer descriptions of documents and links between them. However, in the effort to provide a simple, usable and robust working system, which could be used by everyone 'out-of-the-box', these ideas were put to one side, and the simpler, more human-mediated Web which we know today resulted. But still the content of the Web is not so much rich. To enhance the content of the Web we must use RDF and metadata to make the web more Applicable.

Semantic Web still does not solve the general problem of how to locate and integrate information without human intervention. This is the aim of the semantic Web3 according to the World Wide Web Consortium (W3C) Semantic Web FAQ; the goal is to "allow data to be shared effectively by wider communities, and to be processed automatically by tools as well as manually."

1. Problem Statement

Enhancing Content search using Semantic Web: which will provides an easy-to-use Content Search through which users can find the information they are looking for.

2. Problem Domain

This vision of a semantic Web is extremely motivated and would require solving many long-standing research problems in knowledge representation and reasoning, databases, computational linguistics, computer vision, and agent systems [1]. One such problem is the trade-off between conflicting requirements for expressive power in the language used for semantic annotations and the scalability of the systems used to process them; another is that Integrating different ontologies may prove to be at least as difficult as integrating the resources they describe. Emerging problems include how to create suitable annotations and ontologies and how to deal with the variable quality of Web content. [1]

The content search of web content for large data and information presents enormous resourcing and quality challenges. Users expect to find information quickly, with minimal navigation and with consistency of information and nomenclature. For example content and solutions information, users expect clear, relevant lists of information and services that comprise those solutions, including research papers, publications, videos, images, interviews, conferences and case studies that provide referential examples.

Automated services will improve in their capacity to assist humans in achieving their goals by "understanding" more of the content on the web, and thus providing more accurate filtering, categorization, and searches of information sources. This process will ultimately lead to an extremely knowledgeable system that features various specialized reasoning services. These services will support us in nearly all aspects of our daily life making access to information as pervasive, and necessary, as access to electricity is today.

Applications based on semantic technologies offer new ways to discover, browse and explore information. But how can we (as a semantic web "insider") explain these potential benefits to a typical end-user, who has never heard anything about "faceted search" and Enhance the context of Semantic Web by making Semantic web search Engine more Intelligent and User Friendly.[3]

Here is an example for a mockup of a semantically enhanced Search Engine:

Figure 1: Semantically enhanced Search Engine

3. Background

The Semantic Web augments the current WWW by giving information a well defined meaning, better enabling computers and people to work in cooperation. This is done by adding machine understandable content to Web resources. Such added content is called metadata, whose semantics is provided by referring to ontology—a domain’s conceptualization agreed upon by a community. [5]

Semantic Web was introduced by Tim burners Lee. Semantic Web is related to the "Syntax "how you declare something. Semantic web is the Meaning behind what you Say? Today the web is turning into Semantic Web, even Google support Micro format and RDF in documents and use metadata to make search results more relevant. [1]

According to Tim Berners-Lee,

'The Semantic Web will bring structure to the meaningful content of Web pages, creating an environment where software agents roaming from page to page can readily carry out sophisticated tasks for users.'

4. Research Objectives

Today’s Web is a relatively simple artifact. Web content consist of Hypertext and Hypermedia and it is simply Accessible via Link Navigation, One of the Web Strength is Simplicity even naive users quickly learn to use it and even create their own content. [1] The explosion in both the range and quantity of Web content also highlights serious shortcomings in the hypertext paradigm. The required content becomes increasingly difficult to locate via search and browse. [1] The Objective of this Research is to enhance the content of Web Search by creating suitable annotations and ontologies and how to deal with the variable quality of Web content. [1]

5. Literature Review

Our work is based on Semantic web and to enhance the content of Semantic web by using a technique we prefer paper of Antonio Maria Rinaldi PhD ( Computer engineer , Italy ) he wrote An ontology-driven approach for semantic information retrieval on the Web in ACM Transactions on Internet Technology, Vol. 9, No. 3, Article 10, Publication date was July 2009. In his paper he discussed about Ontology, then how to retrieve data through DSN semantic network and also by use of WordNet to find out the distance between two words. The other paper which we prefer is Improving Web Search Relevance with Semantic Features written by five great scientists from Yahoo Labs Silicon Valley Dr. Yumao Lu (Senior Scientist at Yahoo Labs in Sunnyvale, CA, Ph.D. degree in Electrical Engineering from the University of California Los Angeles in 2005), Dr. Fuchun Peng(Senior Scientist and Manager in Yahoo Search, Ph.D. in computer science from the University of Waterloo, Canada, in 2003),Gilad Mishne(work as query classification, entity detection, and social media applications, PhD from University of Amsterdam 2006, B.Sc. Israel Institute of Technology 2000), Dr. Xing Wei( Scientist in Yahoo Labs, Ph.D. in Computer Science from University of Massachusetts, Amherst in 2007), and Dr. Benoit Dumoulin(Scientist in Yahoo Labs Silicon Valley ) . They wrote paper on Improving Web Search Relevance with Semantic Features and paper was published in Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing in Singapore, 6-7 August 2009. In their paper they also introduce new technology as well as they explain Natural Processing Language and derive semantic text matching features from named entities identified in Web queries; we then utilize these features in a supervised machine-learned ranking approach, applying a set of emerging machine learning techniques.

"Semantic-Powered Research Profiling" this paper is written by Zhixiong Zhang (Director of Information System department at National Science Library), Ying Ding Ph. D (Assistant Professor of Information Science Core Faculty of Cognitive Science), Na Hong (National Science Library Chinese Academy of Sciences); this paper was published at 8th international conference of semantic web 2009. This paper describes a novel infrastructure to generate semantic-powered research profiling for research fields, organizations and individuals. It crawls related websites and news feeds, extracts research terms, research objects and relations from them and uses the proposed Research Ontology to model them into RDF triples to facilitate semantic queries and semantic mining on burst detection, hot topic detection, dynamics of research, and relation mining.

"Semantic Enhancement for Enterprise Data Management" this paper is written by Li Ma, Xingzhi Sun, Feng Cao, Chen Wang, Xiaoyuan Wang, Nick Kanellos,Dan Wolfson, Yue Pan, published at 8th international conference of semantic web 2009.In this paper researchers describes Semantic web technologies by taking customer data as an example, the paper presents an approach to enhance the management of enterprise data by using Semantic Web technologies. Customer data is the most important kind of core business entity a company uses repeatedly across many business processes and systems, and customer data management (CDM) is becoming critical for enterprises because it keeps a single, complete and accurate record of customers across the enterprise.

6. Importance and Benefits of the Study

Let's start with the word semantic. Semantics is the study of language meaning. The Semantic Web is an evolving development of the World Wide Web in which the meaning (semantics) of information and services on the web is defined, making it possible for the web to "understand" and satisfy the requests of people and machines to use the web content. [5][4] It derives from World Wide Web Consortium director Sir Tim Berners-Lee's vision of the Web as a universal medium for data, information, and knowledge exchange. [3]

At its core, the semantic web comprises a set of design principles, [4] collaborative working groups, and a variety of enabling technologies. Our work is based on WordNet and DSN and through these technologies we find out the a solution to enhance the content based search different technologies are used to enhance the content for example using the RDF and Ontologies concept for extracting semantics . Through WorNet as well as if we use Information Retrieval IR to Natural language Processing NLP we can easily extract the content which user is querying for.

In this research we will discuss the strategies and proposed general solutions that can increase the scalability and usability, and also proposed some solutions that can lead the use of semantic web in the future.

7. Research Methodology

Our methodology for this Research Article is Empiricism which arises from sense experience, which is the part epistemology means theory of knowledge, what is knowledge and how it is acquired, what do people know about it. First we will observe the results of Semantic web, and then we will see the results of Content search of semantic web and we will introduce a technique which will enhance the content search of Semantic web.

8. Nature and Form of Results

In this Research Report we will find a technique to enhance the Content search of the Semantic Web and we will apply that technique only on one of the Semantic web based Search Engine and discover the nature of the end result.

9. Qualification of Researcher

We Studied about Semantic Web in the Course of Artificial Intelligence in which one of the member of our Class Presented the topic Semantic Web in which they presented few topics regarding Semantic Web Foundation of Semantic Web, Metadata, RDF, Knowledge Representation, Ontology, Behavioral Intelligence, Semantic Web Stack, Semantic Web Technologies. But in this Research Report we will just focus on the Content Search of Semantic Web and what is the Technique to enhance the Content Search.

10. Budget

We will not be conducting any interview; we will just perform online survey which will not need any cost. Printing Documents is required; cost of Printing Material could be approximately 1000 to 1300 Rupees.

11. Schedule

S.No

Topics

Date

1

Review of Existing search Engines

Feb 2

2

Semantic Web Based Search Engines

Feb 16

3

Semantic search based evolving technologies

Feb 23

4

Enhance the content Search in Semantic Web

March 2

5

To Enhance the content search of a Particular Search Engine with help of Example

March 9

6

Using a technique to Enhance the content search with Example of one Semantic web based Search Engine

March 16

7

Revised Research Report

March 23

8

Submission of Research Report

March 30

12. Glossary

Ontology:

The word refers to the branch of metaphysics that deals with the nature of reality or being. It therefore refers to "what exists" in a system: all elements within all category hierarchies and the relationships between them. [4]

RDF:

Resource Description Framework (RDF), it is the family of World Wide Web designed for metadata model

Metadata:

Metadata is "data about data". It provides information about a certain item's content.

OWL:

Web Ontology Language is designed for use by applications that need to process the content of in order instead of just presenting information to humans.

Faceted search:

Faceted search is also called faceted navigation which allows users to explore by sorting available information.

WWW:

World Wide Web or W3 and commonly known as The Web.

13. References

[1] Horrocks , "Ontologies and the Semantic Web",Communication of the ACM Volume 51, Issue 12, December 2008

[2] Matthews , "Semantic Web Technologies" CCLRC Rutherford Appleton Laboratory May 2009

[3] Ablvienna, "why mockups are essential for semantic applications design". Ablvienna.wordPress. September 17, 2008

[4] Ontology , "Wikipedia", January 11 2010

[5] Shapeshed, "The importance of semantic markup ".10 February 2007

[6] Berners-Lee, "The Semantic Web", Scientific: Scientific American. May 2001

[7] Radhakrishnan, "9 Semantic Search Engines That Will Change the World of Search" Search Engine News, April 13, 2009.

[8] Retrieved from: http://www.searchenginejournal.com/semantic-search engines/9832/

[9] Simmons, "Semantic Web Search Engine Roundup", semantic focus. February 27, 2008 Retrieved from: http://www.semanticfocus.com/blog/entry/title/semantic-web-search-engine-roundup/