Scientific Research Publishing is an academic publisher with more than open access journal in the areas of science, technology and medicine. It also publishes Research Publish Journals is a worldwide open access peer reviewed online International Journal publishing Organisation. It is committed to bring out the highest excellence by publishing unique, novel research articles of upcoming authors as well as renowned scholars. It belongs to an intellectual group of Researchers, Scholars, Industry Experts This paper looks at the literature on establishing a unique field of study, reviews the foundational research in family business (s) and four recent years ( ) of published family business research found in several outlets. We find that family business research is becoming increasingly sophisticated and rigorous
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To browse Academia. edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser. Skip to main content. edu no longer supports Internet Explorer. Log In Sign Up. Download Free PDF. Published research papers. Gagan Narula. Download PDF. Download Full PDF Package This paper. A short summary of this paper. READ PAPER. International Journal of Computer Applications — Volume 94 — No 2, May Improving Statistical Multimedia Information Retrieval MIR Model by using Ontology Gagandeep Singh Narula Vishal Jain B, published research papers.
It also resulted in published research papers. The third model developed is still a cumbersome task. Multimedia documents include was Dublin Core [3] that deals with semantic as well as various elements of different data types including visible and structural content of image and text but it failed to depict audible data types text, images and video documentsrelationship between text and image, published research papers.
structural elements as well as interactive elements. In this With advancement in technology and predictions, some paper, we have proposed a statistical high level multimedia IR probabilistic and futuristic models were also developed.
In model that is unaware of the shortcomings caused by classical following paper, statistical multimedia IR model has been statistical model. It involves use of ontology and different proposed and compared with classical multimedia IR model. published research papers IR approaches Extended Boolean Approach, Bayesian Network Model etc for representation of extracted 1. Human knowledge is richest multimedia storage system.
A typical IR system that delivers and stores information is There are various mechanisms like vision, language that affected by problem of matching between user query published research papers expresses knowledge published research papers information obtained from them available content on web. Use of Ontology represents the must be processed by system efficiently. Published research papers must published research papers extracted terms in form of network graph consisting of nodes, systems designed that interprets and process human queries, edges, index terms etc.
The above mentioned IR approaches thus producing relevant results. baffled while searching results of their queries. The reasons behind this are: The paper also emphasis on analyzing multimedia documents and performs calculation for extracted terms using different The content of information is unclear and needs user statistical formulas.
The proposed model developed reduces to refine that information. semantic gap and satisfies user needs efficiently. Index Terms Information Retrieval IROWL, published research papers, Statistical Approaches BI There lies lower level of interaction between user model, Extended Boolean Approach, published research papers, Bayesian Network request and published research papers information on systems.
The low- ModelQuery Expansion and Refinement. level links are called Semantic Gap. Statistical approaches involves retrieved documents that State of Art matches query closely in terms of statistics i. it must have Research on multimedia information retrieval seems to be statistical model, calculations and analysis. These approaches gargantuan and challenging task. Its areas are so diversified break given query into TERMS.
Terms are words that occur that it has lead to independent research in its own in collection of documents and are extracted automatically. Various experiments information, it is necessary to remove different forms of same and studies were conducted in lieu of these systems, published research papers. The users word because it makes user confused in choosing specific were asked to present a set of valuable things in daily life.
It terms that lies close to query. Some IR systems extract was done on similarity of users. Some of choices are same phrases from documents. A phrase is a combination of two or while some are different.
Few of them prefer to use images more words that is found in document. instead of text caption. We have used approaches like extended Published research papers approach, In further experiments, it was noticed that new users were network model that performs structural analysis for retrieving taking feedback from previous users, published research papers.
It leads to concept of text or image pairs, published research papers. They also assign weights to given term. relevance feedback module in information model. In early The weight is defined as measure of effectiveness of given years, published research papers, most research was done on content- based image term in distinguishing one document from other documents, published research papers. The existing models are of different level and The paper has following sections: Section 2 describes scope.
These models are semantically unambiguous. For e. Section 3 lets IPTC model [1] uses location fields that focus on location of reader go through proposed IR model that is implemented data but this model also failed due to lack of statistical using statistical approaches with the use of ontology.
It also approach. Another metadata model was developed i. Section 4 deals with experimental There is communicational gap between user and analysis and calculations depicting the relevance of proposed system. It is known that some systems are fast in model.
Finally, Section 5 concludes about paper. processing of calculations whereas human is not. So, it leads to communication gap. Model Traditional IR systems are not intelligent that they are able to Since multimedia documents do not contain keywords or produce accurate results. These systems use human perception symbols that facilitates easy process of searching through to process query and returns results, published research papers.
The results may be document. Keeping this in mind, this classical model consists relevant or non- relevant because these systems match query of Published research papers Processing Module that translates the multimedia with information stored in information database.
The model has following modules: The syntax of multimedia document is different from text documents. Multimedia documents do not contain any Analysis Module: - IR system firstly analysis information symbols or keywords that help in expressing multimedia documents and extract features published research papers information.
They consist of: them. The features include low- level as well as high- level features. They called Indexing Module. describe the organization of other data types. They Retrieval Module: - It finds rank of stored communicate variety of messages and emotions that documents on basis of similar terms used in query. helps to understand easily. After ranking of documents, the results satisfying Structure information gives organization and query are presented to user.
usability in performing communications. Multimedia Published research papers Query processing Query Query Indexing Retrieval Application Indexer Results Documents User Multimedia document Figure1: A Classical Multimedia IR Model [5] 2.
They are explained below: The terms which are relevant and similar to each The classical model deals with terms or information other are identified at the end of phase by symbols instead of maintaining relationships RETRIEVAL Module.
The good model is one that between them. It does not give any information has capability to distinguish between relevant and about concepts used in extracted terms or image non relevant terms in the middle of phase in order to pairs. prevent any confusion. Once the query is expanded, it will not information terms stored in information database of store in system for future use, published research papers. Again, it has to IR system.
analyze large collection of documents and retrieve terms from them. In order to overcome this problem, the model includes approaches for determining relevance of IR system. only those approaches that perform extraction of terms like images, video, and text from multimedia documents as well as 3.
PROPOSED HIGH LEVEL text documents, published research papers. Ontology Module has been introduced that serves the task of representing concepts and relationships among retrieved Structure Analysis IR Systems Terms and information Multimedia Published research papers SMART, Indexer Text, Image pairs symbols are extracted.
Use of Statistical approach low- level features as well as Semantic Approach high-level features Statistical Approach Extended Semantic Approach NLP Boolean Approach and Bayesian approaches and knowledge Inference network Model discovery P-norm model BI Model model Extended Boolean Bayesian Network model: It takes Approach: It gives multiple queries at same time.
It n relevant terms creates a graph that has nodes in less time. connected by edges. relevant extracted terms. Classification Algorithm. Extraction of new relevant Creation of new Generate classes from terms and maintaining documents Inference Network graph using semantic associations OWL and XML classes.
Ontology Phrase Extractor INDEXING Query Processing Module Query Processing Query Expansion Query Transformation Rules 1…………………n Uses methods namely Sketch Retrieval, Search by keyword, Search by example, Adaptive retrieval, Transformed queries 1…………. n Local Context Analysis LCA Calculation of new Query Refinement and old weights Dummy document Re-Use of queries. The queries Retrieval Module that are captured are stored in query database for future use.
Only expressive results are presented to user, published research papers. relevant terms are expanded and it leads to saving of Published research papers different modules: - Several modules like time and work.
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4/20/ · These preprints are early stage research papers that have not been peer-reviewed. The findings should not be used for clinical or public health decision making and should not be presented to a lay audience without highlighting that they are preliminary and have not been peer-reviewed. see the comments published in The Lancet about the trial This paper looks at the literature on establishing a unique field of study, reviews the foundational research in family business (s) and four recent years ( ) of published family business research found in several outlets. We find that family business research is becoming increasingly sophisticated and rigorous Published Research We disseminate the results of our work as broadly as possible to benefit the public good. Explore more than 26, RAND publications, most of which are available as free eBook downloads, dating back to
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