A Personalized Ontology Model for Web Information Gathering


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Abstract—As a model for knowledge description and formalization, ontologies are widely used to represent user profiles in
personalized web information gathering. However, when representing user profiles, many models have utilized only knowledge from
either a global knowledge base or a user local information. In this paper, a personalized ontology model is proposed for knowledge
representation and reasoning over user profiles. This model learns ontological user profiles from both a world knowledge base and
user local instance repositories. The ontology model is evaluated by comparing it against benchmark models in web information
gathering. The results show that this ontology model is successful.


INTRODUCTION
ON the last decades, the amount of web-based information
available has increased dramatically. How to
gather useful information from the web has become a
challenging issue for users. Current web information
gathering systems attempt to satisfy user requirements by
capturing their information needs. For this purpose, user
profiles are created for user background knowledge
description [12], [22], [23].



2.2 User Profiles
User profiles were used in web information gathering to
interpret the semantic meanings of queries and capture user
information needs [12], [14], [23], [41], [48]. User profiles
were defined by Li and Zhong [23] as the interesting topics
of a user’s information need. They also categorized user
profiles into two diagrams: the data diagram user profiles
acquired by analyzing a database or a set of transactions
[12], [23], [25], [35], [37]; the information diagram user
profiles acquired by using manual techniques, such as
questionnaires and interviews [25], [41] or automatic
techniques, such as information retrieval and machine
learning [30]. Van der Sluijs and Huben [43] proposed a
method called the Generic User Model Component to
improve the quality and utilization of user modeling.


3 PERSONALIZED ONTOLOGY CONSTRUCTION
Personalized ontologies are a conceptualization model that
formally describes and specifies user background knowledge.
From observations in daily life, we found that web
users might have different expectations for the same search
query. For example, for the topic “New York,” business
travelers may demand different information from leisure
travelers. Sometimes even the same user may have different
expectations for the same search query if applied in a
different situation. A user may become a business traveler
when planning for a business trip, or a leisure traveler when
planning for a family holiday. Based on this observation, an
assumption is formed that web users have a personal
concept model for their information needs.


3.1 World Knowledge Representation
World knowledge is important for information gathering.
According to the definition provided by [46], world
knowledge is commonsense knowledge possessed by
people and acquired through their experience and education.
Also, as pointed out by Nirenburg and Raskin [29],
“world knowledge is necessary for lexical and referential
disambiguation, including establishing coreference relations
and resolving ellipsis as well as for establishing and
maintaining connectivity of the discourse and adherence of
the text to the text producer’s goal and plans.” In this
proposed model, user background knowledge is extracted
from a world knowledge base encoded from the Library of
Congress Subject Headings (LCSH).