3. Introduction
Information retrieval is the activity of obtaining information
resources relevant to an information need from a collection of
information resources.
An information retrieval process begins when a user enters a
query into the system. Queries are formal statements of
information needs.
User queries are matched against the database information.
Depending on the application the data objects may be, for
example, text documents, images, audio, mind maps or
videos.
Most IR systems compute a numeric score on how well each
object in the database matches the query, and rank the objects
according to this value.
The top ranking objects are then shown to the user. The
process may then be iterated if the user wishes to refine the
query.
4. IRS Definitions
“Information retrieval embraces the
intellectual aspects of the description
of information and its specification for
search, and also whatever systems,
techniques, or machines are
employed to carry out the operation.”
Calvin Mooers, 1951
Objective:
Provide the users with effective access
to & interaction with information
resources.
5. Three major components
1. Document subsystem
a) Acquisition
b) Representation
c) File organization
2. User sub system
a) Problem
b) Representation
c) Query
3. Searching /Retrieval subsystem
a) Matching
b) Retrieved objects
7. Basic concepts
[Baeza-Yates et al., 1999] gives a basic introduction to the
concepts of Information Retrieval. The use of Information
Retrieval is motivated by an information need. This information need
can be explicitly or implicitly verbalized. In a ‘real world’ setting the
person seeking information (i.e. the user) formulates such a question
and poses it to an expert. The expert calls upon his internal
representation of the knowledge space and external documents and
formulates answers. From the answers received the user extracts
relevant points and gives feedback to the expert. This
“conversational loop” can also be found in the use of an Information
Retrieval System (IRS). As the IRS is not capable to understand the
information need, an abstraction matching the IRS is needed. This
abstraction is called query. Analogously to the expert, the IRS
formulates an answer based upon the internal representation of the
knowledge space and external documents. The answer is composed
of documents perceived relevant or links to such documents. The
user extracts those documents that are indeed relevant. In some
systems relevance feedback can be given. These two forms of the
conversational loop are detailed in Figure 2.2.
9. Objectives
Highlight influential work on probabilistic
models for IR
Provide a working understanding of the
probabilistic techniques through a set of
common implementation tricks
Establish relationships between the
popular approaches: stress common
ideas, explain differences Outline issues
in extending the models to interactive,
cross-language, multi-media.
10. Functions :
An information retrieval system deals with
various sources of information on the one hand
and users’ requirements on the other. It must:
► Analyze the contents of the sources of
information as well as the users’ queries,
and then
► Match these to retrieve those items that are
relevant.
Information retrieval systems have the following
functions:
► To identify the information (sources) relevant to
the areas of interest of the target users’
community; this is a challenging job especially in
the web
11. Conclusion :
The field of information retrieval has come a
long way in the last forty years, and has enabled
easier and faster information discovery. However,
for the task of finding information, these
statistical techniques have Indeed proven to be
the most effective ones so far. Techniques
developed in the field have been used in many
other areas and have yielded many new
technologies which are used by people on an
everyday basis, e.g., web search engines, junk-
email filters, news clipping services. Going
forward, the field is attacking many critical
problems that users face in today's information-
ridden world. With exponential growth in the
amount of information available, information
retrieval will play an increasingly important role in
future.
