International Journal of Emerging Technologies and Engineering (IJETE) Volume 1 Issue 10, November 2014, ISSN 2348 – 8050

253

www.ijete.org

Content Search & Query Value Search for Document Annotation

Nishigandha Kute*, Monal Salunke**, Surekha Khaire***

,Prof. Mrs. S. Patil****

*MMIT, Savitribai Phule Pune University, Lohgaon ** MMIT, Savitribai Phule Pune University, Lohgaon

*** MMIT, Savitribai Phule Pune University, Lohgaon **** MMIT, Department of Computer Engineering, Savitribai Phule Pune University, Lohgaon

ABSTRACT Searching the World Wide Web can be both beneficial and frustrating in today’s life. And also all collection of textual data contains large amount of structured information which remains hidden in unstructured format. Relevant information is always difficult to find in these documents. You may find vast amounts of information, or you may not find the kinds of information you're looking for. Searching online will provide you with a wealth of information, but not all of it will be useful or of the highest quality. In this paper we are consider an alternative approach for content and query searching based on Facilitating Document Annotation for the structured metadata by identifying documents in overall system that are likely to contain information of interest and this information is going to be useful for content of querying the database. Here publisher will likely to assign metadata, structured or unstructured related to documents which they upload which will easily help the users in retrieving the documents. Keywords – CADs, Annotation, Query,Attribute

I. INTRODUCTION

Enhancing the search results in large archives is a concern shared by Collection of huge and textual data. The search content improvement can come from two directions of method: Filename based search or Content based search. Both search content directions are active research areas. In this filename based search system are search the data within the filename itself and it produces very low accurate results. And second one is content based search the data within the file contents instead of filename. It also produces very low accurate and large amount of results. But there is no any use of the results. In this paper we learn and explore the interaction between Document Annotation Using Content & Querying Value.

II. ANNOTATION OF DOCUMENT

Annotations of documents are comments, notes, explanations, or other types of external remarks that can be attached to a Web document or to a selected part of a document. As they are external, it is possible to annotate any Web document independently, without needing to edit the document itself. From a technical point of view, annotations are usually seen as metadata, as they give additional information about an existing piece of data. Annotations of documents can be stored locally or in one or more database servers. When a document is searched, content of queries value each of these database servers, requesting the annotations related to that document in web server database. An annotation has many properties including: Document

Annotation Physical location: is the publisher stored in the local file system or in a database server Document Annotation Scope : is the user associated to a whole document or just to a fragment. Document Annotation type : 'Annotation', 'Comment', 'Query', 'Content'...

III. PROPOSED WORK

In Proposed System or in this paper, we describe CADS (Collaborative Adaptive Data Sharing platform), which is based on an “annotate-as-you-create” infrastructure that facilitates fielded data annotation document. A key or query content contribution of our system is the direct use of the query for annotation process, in addition to examining the content of the document. In other collection of textual words, we are trying to prioritize the annotation of documents towards generating attribute values for attributes that are often used by content querying users.

IV. ALGORITHM IMPLEMENTATION

4.1 INFORMATION EXTRACTION :

International Journal of Emerging Technologies and Engineering (IJETE) Volume 1 Issue 10, November 2014, ISSN 2348 – 8050

254

www.ijete.org

Information extraction (IE) systems: Step 1: Find and understand limited relevant parts of texts in annotation documents Step 2: Gather information from many pieces of textual data or documents Step3: Produce a structured representation of relevant information from the document: -relations (in the database sense), a.k.a., -a knowledge base

4.2 QV, CV COMPUTATION AND COMBINING

ALGORITHM:

Step 1: Enter the content queries as input for retrieving document form the given attribute Example : College='MMIT' and address='Lohgaon' Step 2: Divide the quires and send to or pass it to database for retrieving Step 3: Check all annotation document related results and show the related result from the database to user Step 4: The efficient and accurate and correct result, users should try to enter maximum queries they can

V. SYSTEM ARCHITECTURE

We describe the actual working of the system.

This system is very useful for users. This system describes the Document Annotation Using Content & Querying for based on online and offline system. It is also useful for publisher or author of annotation document. Show the following module for system.

Modules:

1. User or Publisher Registration

2. User or Publisher Login

3. Document Upload By Publisher (Author)

4. Content & Querying Search Techniques

5. Get (Show) Result

Modules Description

User or Publisher Registration:

In this module Publisher (Creator) or User

have to register first, then only registered user or publisher

has to access the data base from the system.

User or Publisher Login:

In this module registered person has login to

database for purpose of authentication and then entered in

the system as user or publisher.

Document Upload By Publisher (Author) :

In this module publisher uploads an unstructured

document as file(along with meta data) into system

database, with the help of this metadata and its Document

Annotation Using Content , the end user has to download

the file on the system . User or publisher has to enter

content/query for download the file.

Fig1.1 System Architecture

International Journal of Emerging Technologies and Engineering (IJETE) Volume 1 Issue 10, November 2014, ISSN 2348 – 8050

255

www.ijete.org

Content & Querying Search Techniques :

Here we are using two techniques for

searching the annotation document first one is Content

Search, second one is Query Search. In the content search

document will be downloaded by giving the content

search which is present in the corresponding annotation

document. If its search result present the corresponding

document will be downloaded, otherwise it is not

downloaded. And second one is query search that the

document will downloaded by using simple query which

has present in the base paper .if the result is matches the

document then this document will be downloaded

otherwise it rejected.

Show Result and Download Document:

The User or publisher has to download the document

using query search /content search values which have

given in the base paper or the database .user or publisher

enters the correct data in the text boxes, if its correct or

matches it will download the document file. Otherwise it

is rejected.

VI CONCLUSION

We presented in this paper the two ways to combine these

two techniques of evidence, content value search and

querying value search. The main use of our system is

mainly that when users of author perform query based

search, they could get minimum and distinct accurate

results where it could be easy for retrieval data from the

database. By using these techniques two techniques,

workload of system can reduce by large amount. And it

Also, given the fact the efficiency of searching annotation

document will be faster because of using the query-based

searching technique or content value searching .

Query-based searching will be the future in

information retrieval from the database as this searching

techniques may be applied on other file formats like

.docx,.pdf,.xml etc which can give users better, faster and

accurate results produce and will also increase the

performance of system or application . This system gets

the good result for searching of database.

REFERENCES

[1] Eduardo J. Ruiz, Vangelis Hristidis, Panagiotis G. Ipeirotis, “Facilitating Document Annotation using Content and Querying Value”, ieee transactions on knowledge and data engineering vol.pp no.99 2013.

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Collaborative Adaptive Data Sharing Platform”, School of

Computing and Information Sciences, Florida

International University.

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