| Authors: |
Alessandro Micarelli
and Filippo Sciarrone
and Mauro Marinilli
|
| Editors: |
Peter Brusilovsky
and Alfred Kobsa
and Wolfgang Nejdl
|
| URL: |
http://dx.doi.org/10.1007/978-3-540-72079-9_5 |
| Tags: |
adaptive
ai
data
document
information
knowledge
paper
processing
retrieval
springer
v0805
web
|
| Abstract: |
A very common issue of adaptive Web-Based systems is the modeling
of documents. Such documents represent domain-specific information
for a number of purposes. Application areas such as Information Search,
Focused Crawling and Content Adaptation (among many others) benefit
from several techniques and approaches to model documents effectively.
For example, a document usually needs preliminary processing in order
to obtain the relevant information in an effective and useful format,
so as to be automatically processed by the system. The objective
of this chapter is to support other chapters, providing a basic overview
of the most common and useful techniques and approaches related with
document modeling. This chapter describes high-level techniques to
model Web documents, such as the Vector Space Model and a number
of AI approaches, such as Semantic Networks, Neural Networks and
Bayesian Networks. This chapter is not meant to act as a substitute
of more comprehensive discussions about the topics presented. Rather,
it provides a brief and informal introduction to the main concepts
of document modeling, also focusing on the systems that are presented
in the rest of the book as concrete examples of the related concepts. |
@incollection{MicarelliSciarroneMarinilli07p155,
title = {Web Document Modeling},
address = {Berlin, Heidelberg},
author = {Alessandro Micarelli and Filippo Sciarrone and Mauro Marinilli},
booktitle = {The Adaptive Web: Methods and Strategies of Web Personalization},
chapter = {5},
crossref = {BrusilovskyKobsaNejdl2007},
editor = {Peter Brusilovsky and Alfred Kobsa and Wolfgang Nejdl},
pages = {155-192},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
url = {http://dx.doi.org/10.1007/978-3-540-72079-9_5},
volume = {4321},
year = {2007},
abstract = {A very common issue of adaptive Web-Based systems is the modeling
of documents. Such documents represent domain-specific information
for a number of purposes. Application areas such as Information Search,
Focused Crawling and Content Adaptation (among many others) benefit
from several techniques and approaches to model documents effectively.
For example, a document usually needs preliminary processing in order
to obtain the relevant information in an effective and useful format,
so as to be automatically processed by the system. The objective
of this chapter is to support other chapters, providing a basic overview
of the most common and useful techniques and approaches related with
document modeling. This chapter describes high-level techniques to
model Web documents, such as the Vector Space Model and a number
of AI approaches, such as Semantic Networks, Neural Networks and
Bayesian Networks. This chapter is not meant to act as a substitute
of more comprehensive discussions about the topics presented. Rather,
it provides a brief and informal introduction to the main concepts
of document modeling, also focusing on the systems that are presented
in the rest of the book as concrete examples of the related concepts.},
timestamp = {2008.02.10}, file = {SpringerLink:2007/MicarelliSciarroneMarinilli07p155.pdf:PDF}, isbn = {978-3-540-72078-2}, owner = {flint},
keywords = {adaptive ai data document information knowledge paper processing retrieval springer v0805 web }
}
::