TITLE:
Content Based Segregation of Pertinent Documents Using Adaptive Progression
AUTHORS:
Perumal Pitchandi, Sreekrishna Muthukumaravel, Suganya Boopathy
KEYWORDS:
Document Annotation, Segregation, Identification, Content Type
JOURNAL NAME:
Circuits and Systems,
Vol.7 No.8,
June
22,
2016
ABSTRACT: Due to the emerging
technology era, today a number of firms share their service/product
descriptions. Such a group of information in the textual form has some
structured information, which is beneath the unstructured text. A new
attainment which facilitates the form of a structured metadata by recognizing
documents which are likely to have some type and this information is then used
for both segregation and search process. The idea of this advent describes some
attributes of a text that will match with the query object which acts as
identifier both for segregation as well as for storage and retrieval. An
adaptive technique is proposed to deal with relevant attributes to annotate a
document by satisfying the users querying needs. The solution for
annotation-attribute suggestion problem is not based on the probabilistic model
or prediction but it is based on the basic keywords that a user can use to
query a database to retrieve a document. Experiment results show that Querying
value and Content Value approach is much useful in predicting a tag for a
document and thus prediction is also based on Querying value and Content value
which greatly improves the utility of shared data which is a drawback in the
existing system. This approach is different, as we consider only the basic
keywords to be matched with the content of a document. When compared with other
approaches in the existing system, Clarity is a primary goal as we expect that
the annotator may improve the annotations on process. The discovered tags
assist on quest of retrieval as an alternative to bookmarking.