Paper Presented in National Seminar on
Networking of Library and Information Centres of North East India in Digital Environment (NLICDE-2011)
(21-23 March 2011)ORGANISED UNDER THE AEGIS OF National Library, Kolkata
Ministry of Culture, Govt. of IndiaByOrganized by
Central Library, National Institute of Technology Silchar
Paper Presented in National Seminar on
Networking of Library and Information Centres of North East India in Digital Environment (NLICDE-2011)
(21-23 March 2011)ORGANISED UNDER THE AEGIS OF National Library, Kolkata
Ministry of Culture, Govt. of IndiaByOrganized by
Central Library, National Institute of Technology Silchar
It destroys your appetite, burns the fat you just can’t seem to lose, and sends your energy levels through the roof. If you’re looking for something new to attack the fat, look no further. WeightLoss Green Store Tea contains cutting edge ingredients, making it stand apart from the rest of the fat burners out there.
Semantic Web: Technolgies and Applications for Real-WorldAmit Sheth
Amit Sheth and Susie Stephens, "Semantic Web: Technolgies and Applications for Real-World," Tutorial at 2007 World Wide Web Conference, Banff, Canada.
Tutorial discusses technologies and deployed real-world applications through 2007.
Tutorial description at: http://www2007.org/tutorial-T11.php
It destroys your appetite, burns the fat you just can’t seem to lose, and sends your energy levels through the roof. If you’re looking for something new to attack the fat, look no further. WeightLoss Green Store Tea contains cutting edge ingredients, making it stand apart from the rest of the fat burners out there.
Semantic Web: Technolgies and Applications for Real-WorldAmit Sheth
Amit Sheth and Susie Stephens, "Semantic Web: Technolgies and Applications for Real-World," Tutorial at 2007 World Wide Web Conference, Banff, Canada.
Tutorial discusses technologies and deployed real-world applications through 2007.
Tutorial description at: http://www2007.org/tutorial-T11.php
The Semantic Web is a vision of information that is understandable by computers. Although there is great exploitable potential, we are still in "Generation Zero'' of the Semantic Web, since there are few real-world compelling applications. The heterogeneity, the volume of data and the lack of standards are problems that could be addressed through some nature inspired methods. The paper presents the most important aspects of the Semantic Web, as well as its biggest issues; it then describes some methods inspired from nature - genetic algorithms, artificial neural networks, swarm intelligence, and the way these techniques can be used to deal with Semantic Web problems.
Semantic Query Optimisation with Ontology Simulationdannyijwest
Semantic Web is, without a doubt, gaining momentum in both industry and academia. The word “Semantic” refers to “meaning” – a semantic web is a web of meaning. In this fast changing and result oriented practical world, gone are the days where an individual had to struggle for finding information on the Internet where knowledge management was the major issue. The semantic web has a vision of linking, integrating and analysing data from various data sources and forming a new information stream, hence a web of databases connected with each other and machines interacting with other machines to yield results which are user oriented and accurate. With the emergence of Semantic Web framework the naïve approach of searching information on the syntactic web is cliché. This paper proposes an optimised semantic searching of keywords exemplified by simulation an ontology of Indian universities with a proposed algorithm which ramifies the effective semantic retrieval of information which is easy to access and time saving.
"At the toolbar (menu, whatever) associated with a document there is a button marked "Oh, yeah?". You press it when you lose that feeling of trust. It says to the Web, 'so how do I know I can trust this information?'. The software then goes directly or indirectly back to metainformation about the document, which suggests a number of reasons."
Tim Berners-Lee, W3C Chair, Web Design Issues, September 1997
Provenance is focused on the description and understanding of where and how data is produced, the actors involved in the production of such data, and the processes by which the data was manipulated and transformed until it arrived to the collection from which it is being accessed. Provenance aims at providing the ability to trace the sources of data, enabling the exploration not just of the relationships between datasets, but also of their authors and affiliations, with the goal of preserving data ownership and establishing a notion of trust based on authenticity and reliability.
The Future Internet poses important challenges for provenance, derived from complex and rich scenarios characterized by the presence of large amounts of data stemming from heterogeneous sources like user communities, services, and things. Such challenges span across technical but also socioeconomic dimensions. The former includes aspects like vocabularies for representing provenance, interoperability and scalability issues, and means to produce, acquire, and reason with provenance in order to provide measures of trust and information quality. However, it is probably in the socieconomic dimension where more significant efforts need to be made as to addressing issues like the role of provenance in the overall picture of the Future Internet, entry barriers preventing the generation of provenance-aware internet content, means required to incentivate the production of such content, and ways to prevent provenance forgery.
In this talk, we provide and overview on provenance and the above mentioned challenges and introduce ongoing work in order to address trust issues from the provenance perspective in the Future Internet. We also link provenance to other relevant aspects for trust discussed in the session, like security, legal frameworks, and economics.
Mending the Gap between Library's Electronic and Print Collections in ILS and...New York University
This presentation proposed a conceptual model to model user's info seeking behavior in the context of their experience and use the model to improve library's collections and services using St. John's University Libraries for case study. It reviewed Web content technologies offered by IT vendors, and compared what offered in content technologies by Library IT vendors. To fill in the gap, It developed the preliminary proposal for 1) required data architecture in SOA framework, 2) desired features for managing library print and electronic content on library's website, 3) adoption of Semantic Web standards and technologies for managing library resources, and 4) the case study scenario with sample conceptual model.
Ontology Based Approach for Semantic Information Retrieval SystemIJTET Journal
Abstract—The Information retrieval system is taking an important role in current search engine which performs searching operation based on keywords which results in an enormous amount of data available to the user, from which user cannot figure out the essential and most important information. This limitation may be overcome by a new web architecture known as the semantic web which overcome the limitation of the keyword based search technique called the conceptual or the semantic search technique. Natural language processing technique is mostly implemented in a QA system for asking user’s questions and several steps are also followed for conversion of questions to the query form for retrieving an exact answer. In conceptual search, search engine interprets the meaning of the user’s query and the relation among the concepts that document contains with respect to a particular domain that produces specific answers instead of showing lists of answers. In this paper, we proposed the ontology based semantic information retrieval system and the Jena semantic web framework in which, the user enters an input query which is parsed by Standford Parser then the triplet extraction algorithm is used. For all input queries, the SPARQL query is formed and further, it is fired on the knowledge base (Ontology) which finds appropriate RDF triples in knowledge base and retrieve the relevant information using the Jena framework.
An efficient educational data mining approach to support e-learningVenu Madhav
The e-learning is a recent development that has
emerged in the educational system due to the growth of the
information technology. The common challenges involved
in The e-learning platform include the collection and
annotation of the learning materials, organization of the
knowledge in a useful way, the retrieval and discovery of
the useful learning materials from the knowledge space in a
more significant way, and the delivery of the adaptive and
personalized learning materials. In order to handle these
challenges, the proposed system is developed using five
different steps of knowledge input such as the annotation of
the learning materials, creation of knowledge space,
indexing of learning materials using the multi-dimensional
knowledge and XML structure to generate a knowledge
grid and the retrieval of learning materials performed by
matching the user query with the indexed database and
ontology. The process is carried out in two modules such as
the server module and client module. The proposed
approach is evaluated using various parameters such as the
precision, recall and F-measure. Comprehensive results are
achieved by varying the keywords, number of documents
and the K-size. The proposed approach has yielded
excellent results by obtaining the higher evaluation metric,
together with an average precision of 0.81, average
AHM 2014: OceanLink, Smart Data versus Smart Applications EarthCube
Presentation given by Krysztof Janowicz and Pascal Hitzler in the afternoon Architecture Forum Session on Day 1, June 24, at the EarthCube All-Hands Meeting.
Data Mining on Web URL Using Base 64 Encoding to Generate Secure URNIJMTST Journal
The current Web has no general mechanisms to make digital artifacts such as datasets, code, texts, and images verifiable and permanent. For digital artifacts that are supposed to be immutable, there is moreover no commonly accepted method to enforce this immutability. These shortcomings have a serious negative impact on the ability to reproduce the results of processes that rely on Web resources, which in turn heavily impacts areas such as science where reproducibility is important. To solve this problem, we propose trusty URIs containing cryptographic hash values. We show how trusty URIs can be used for the verification of digital artifacts, in a manner that is independent of the serialization format in the case of structured data files such as nano publications. We demonstrate how the contents of these files become immutable, including dependencies to external digital artifacts and thereby extending the range of verifiability to the entire reference tree. Our approach sticks to the core principles of the Web, namely openness and decentralized architecture, and is fully compatible with existing standards and protocols.
Mining in Ontology with Multi Agent System in Semantic Web : A Novel Approachijma
A large amount of data is present on the web. It contains huge number of web pages and to find suitable
information from them is very cumbersome task. There is need to organize data in formal manner so that
user can easily access and use them. To retrieve information from documents, there are many Information
Retrieval (IR) techniques. Current IR techniques are not so advanced that they can be able to exploit
semantic knowledge within documents and give precise results. IR technology is major factor responsible
for handling annotations in Semantic Web (SW) languages. With the rate of growth of web and huge
amount of information available on the web which may be in unstructured, semi structured or structured
form, it has become increasingly difficult to identify the relevant pieces of information on the internet. IR
technology is major factor responsible for handling annotations in Semantic Web (SW) languages.
Knowledgeable representation languages are used for retrieving information. So, there is need to build an
ontology that uses well defined methodology and process of developing ontology is called Ontology
Development. Secondly, Cloud computing and data mining have become famous phenomena in the current
application of information technology. With the changing trends and emerging of the new concept in the
information technology sector, data mining and knowledge discovery have proved to be of significant
importance. Data mining can be defined as the process of extracting data or information from a database
which is not explicitly defined by the database and can be used to come up with generalized conclusions
based on the trends obtained from the data. A database may be described as a collection of formerly
structured data. Multi agents data mining may be defined as the use of various agents cooperatively
interact with the environment to achieve a specified objective. Multi agents will always act on behalf of
users and will coordinate, cooperate, negotiate and exchange data with each other. An agent would
basically refer to a software agent, a robot or a human being Knowledge discovery can be defined as the
process of critically searching large collections of data with the aim of coming up with patterns that can be
used to make generalized conclusions. These patterns are sometimes referred to as knowledge about the
data. Cloud computing can be defined as the delivery of computing services in which shared resources,
information and software’s are provided over a network, for example, the information super highway.
Cloud computing is normally provided over a web based service which hosts all the resources required. As,
the knowledge mining is used in many fields of study such as in science and medicine, finance, education,
manufacturing and commerce. In this paper, the Semantic Web addresses the first part of this challenge by
trying to make the data also machine understandable in the form of Ontology, while Multi-Agen
Mining in Ontology with Multi Agent System in Semantic Web : A Novel Approach
SEMANTIC WEB
1. Ridhyee U. Dabholkar
Under the Guidance:
Prof. Praveen Chitti
JGI’s
Jain College of Engineering, Belgaum. 1
2. 2
Semantic Web Architecture
What Is Semantic Web?
Today’s Web And It’s Limitations
Challenges
References
Conclusion
Benefits
Building Blocks
Skeptical Reactions
Supporting Multiple Distributed Environment
3. “The Semantic Web is an
extension of the current web in
which information is given well-
defined meaning, better enabling
computers and people to work in
co-operation.“
3
4. Quality of information resources is not reliable and
accurate.
Searching of information can be tedious.
Internet is not secure.
Performance and speed .
4
6. URI
– A universal resource identifier (URI)
– Means of identifying abstract or physical
resource
Unicode
– Unicode provides a unique number
XML and XML Namespace
– XML (eXtensible markup language
– Common syntax is used in the semantic
Web
6
7. RDF and RDF Schema
– Resource Description Framework (RDF)
– Based on triples-O, A and V
Ontology
– Ontology comprises a set of knowledge
terms
– Ontology's applied to the Web are creating
the semantic Web
Logic, Proof, Trust and Digital
Signature
– Used to enhance the ontology language
further
– To allow the writing of application-specific
7
13. Is not as complex as people believe.
Doesn’t require huge investments before
seeing its value.
For that reason, take this advice as a
collection of guidelines instead of a hard set of
rules.
13
