|
Introduction
Most keyword-based information retrieval systems have limited
facilities to accept and process a user’s intention.
The user’s request is commonly provided by terms, phrases,
or sentences. There is no accommodation for a system to collect
and analyze the user’s intention. In order to analyze
the user’s intention, we adopt user modeling scheme.
The goal of user model is to accurately capture and represent
a user’s intent. User modeling techniques have been
exploited to help users, including analysts, improve their
performance since the late 80s (Brajnik et al 1987). The successful
user model should be an answer to improve retrieval performance
and satisfies users simultaneously.
Philosophy for quantifying the generality
In the traditional information retrieval systems, index terms
are used to index and retrieve documents. An index term is
a keyword (or a group of related words) whose semantic reference
serves as a mnemonic device for recalling the main themes
of the document. Thus, an index term set is simply keywords
which appears in the text of document in the collection. The
index term set is attached to each sub collection that is
built by ontology mechanism.
Within this philosophy, the degree of generality can be quantified
by the amount of the index terms in the document that belong
to specific word sets. The degree of generality can be quantified
by the amount of the index terms in the document that belong
to specific word sets. The specific word set is a sub set
of the index term set that is not appeared in other sub collections
(ontology node). A specific word set of each node consists
of index terms that do not belong to the index terms set in
other node. For example, a node has its own index term set
. Then a specific term set is a set of index terms that are
not belonging to index term sets in other nodes.
The Figure 1 illustrated a diagram of the degree of generality
in document . In the figure, and are two different ontology
nodes (or clusters). The document is an instance of . Therefore,
the degree of generality for the document is presented by
the dark gray portion. The specific word set of is presented
by the light gray portion
Figure 1 A diagram
presentation for the degree of generality for the document
The goal of this study is to introduce, define
and quantify the degree of generality to find relevant information
in response to a user’s intent. Since the traditional
meaning of the relevance is not sufficient to satisfy the
user’s intent to find the appropriate information, or
to retrieve the relevant information, we need an additional
criterion called “generality” to improve the retrieval
results.
|
