The document discusses the history and components of information retrieval systems. It defines information retrieval as searching a collection of documents to identify those related to a topic. Modern systems can retrieve multimedia content like text, audio, images and video. The key components are the document subsystem that analyzes and stores content, the user subsystem that analyzes queries, and the retrieval subsystem that matches queries to documents. The purpose is to connect those generating information with those needing it.
Information Storage and Retrieval : A Case StudyBhojaraju Gunjal
Bhojaraju.G, M.S.Banerji and Muttayya Koganurmath (2004). Information Storage and Retrieval: A Case Study, In Proceedings of International Conference on Digital Libraries (ICDL 2004), New Delhi, Feb 24-27, 2004.
(Best Poster Presentation Award)
MLIS Course Code 5501-Information Retrieval and Dissemination- Workshop AIOU 2013, Information Management, Information Retrieval and Dissemination, Information Retrieval, Information Dissemination, Workshop, AIOU, Computer Science, Information science, Information technology, Hardware, Software, Computer basics,
Information Storage and Retrieval : A Case StudyBhojaraju Gunjal
Bhojaraju.G, M.S.Banerji and Muttayya Koganurmath (2004). Information Storage and Retrieval: A Case Study, In Proceedings of International Conference on Digital Libraries (ICDL 2004), New Delhi, Feb 24-27, 2004.
(Best Poster Presentation Award)
MLIS Course Code 5501-Information Retrieval and Dissemination- Workshop AIOU 2013, Information Management, Information Retrieval and Dissemination, Information Retrieval, Information Dissemination, Workshop, AIOU, Computer Science, Information science, Information technology, Hardware, Software, Computer basics,
Comparison of Semantic and Syntactic Information Retrieval System on the basi...Waqas Tariq
In this paper information retrieval system for local databases are discussed. The approach is to search the web both semantically and syntactically. The proposal handles the search queries related to the user who is interested in the focused results regarding a product with some specific characteristics. The objective of the work will be to find and retrieve the accurate information from the available information warehouse which contains related data having common keywords. This information retrieval system can eventually be used for accessing the internet also. Accuracy in information retrieval that is achieving both high precision and recall is difficult. So both semantic and syntactic search engine are compared for information retrieval using two parameters i.e. precision and recall.
Decision Support for E-Governance: A Text Mining ApproachIJMIT JOURNAL
Information and communication technology has the capability to improve the process by which governments involve citizens in formulating public policy and public projects. Even though much of government regulations may now be in digital form (and often available online), due to their complexity and diversity, identifying the ones relevant to a particular context is a non-trivial task. Similarly, with the advent of a number of electronic online forums, social networking sites and blogs, the opportunity of gathering citizens’ petitions and stakeholders’ views on government policy and proposals has increased greatly, but the volume and the complexity of analyzing unstructured data makes this difficult. On the other hand, text mining has come a long way from simple keyword search, and matured into a discipline capable of dealing with much more complex tasks. In this paper we discuss how text-mining techniques can help in retrieval of information and relationships from textual data sources, thereby assisting policy makers in discovering associations between policies and citizens’ opinions expressed in electronic public forums and blogs etc. We also present here, an integrated text mining based architecture for e-governance decision support along with a discussion on the Indian scenario.
Metadata is the information that is embedded
in a file whose contents are the explanation of the file. In the
handling of the main evidence with a metadata-based approach
is still a lot of manually in search for correlation related files to
uncover various cases of computer crime. However, when
correlated files are in separate locations (folders) and the
number of files will certainly be a formidable challenge for
forensic investigators in analyzing the evidence. In this study,
we will build a prototype analysis using a metadata-based
approach to analyze the correlation of the main proof file with
the associated file or deemed relevant in the context of the
investigation automatically based on the metadata parameters
of Author, Size, File Type and Date. In this research, the
related analysis read the characteristics of metadata file that is
file type Jpg, Docx, Pdf, Mp3 and Mp4 and analysis of digital
evidence correlation by using specified parameters, so it can
multiply the findings of evidence and facilitate analysis of
digital evidence. In this research, the result of correlation
analysis of digital evidence found that using parameter of
Author, Size, File Type and Date found less correlated file
while using parameter without Size and File Type found more
correlated file because of various extension and file size.
Classification-based Retrieval Methods to Enhance Information Discovery on th...IJMIT JOURNAL
The widespread adoption of the World-Wide Web (the Web) has created challenges both for society as a whole and for the technology used to build and maintain the Web. The ongoing struggle of information retrieval systems is to wade through this vast pile of data and satisfy users by presenting them with information that most adequately it’s their needs. On a societal level, the Web is expanding faster than we can comprehend its implications or develop rules for its use. The ubiquitous use of the Web has raised important social concerns in the areas of privacy, censorship, and access to information. On a technical level, the novelty of the Web and the pace of its growth have created challenges not only in the development of new applications that realize the power of the Web, but also in the technology needed to scale applications to accommodate the resulting large data sets and heavy loads. This thesis presents searching algorithms and hierarchical classification techniques for increasing a search service's understanding of web queries. Existing search services rely solely on a query's occurrence in the document collection to locate relevant documents. They typically do not perform any task or topic-based analysis of queries using other available resources, and do not leverage changes in user query patterns over time. Provided within are a set of techniques and metrics for performing temporal analysis on query logs. Our log analyses are shown to be reasonable and informative, and can be used to detect changing trends and patterns in the query stream, thus providing valuable data to a search service.
Enhanced Performance of Search Engine with Multitype Feature Co-Selection of ...IJASCSE
Information world meet many confronts nowadays and one such, is data retrieval from a multidimensional and heterogeneous data set. Han & et al carried out a trail for the mentioned challenge. A novel feature co-selection for web document clustering is proposed by them, which is called Multitype Features Co-selection for Clustering (MFCC). MFCC uses intermediate clustering results in one type of feature space to help the selection in other types of feature spaces. It reduces effectively of the noise introduced by “pseudoclass” and further improves clustering performance. This efficiency also can be used in data retrieval, by implementing the MFCC algorithm in ranking algorithm of Search Engine technique. The proposed work is to apply the MFCC algorithm in search engine architecture. Such that the information retrieves from the dataset is retrieved effectively and shows the relevant retrieval.
Web personalization using clustering of web usage dataijfcstjournal
The exponential growth in the number and the complexity of information resources and services on the Web
has made log data an indispensable resource to characterize the users for Web-based environment. It
creates information of related web data in the form of hierarchy structure through approximation. This
hierarchy structure can be used as the input for a variety of data mining tasks such as clustering,
association rule mining, sequence mining etc.
In this paper, we present an approach for personalizing web user environment dynamically when he
interacting with web by clustering of web usage data using concept hierarchy. The system is inferred from
the web server’s access logs by means of data and web usage mining techniques to extract the information
about users. The extracted knowledge is used for the purpose of offering a personalized view of the
services to users.
Comparison of Semantic and Syntactic Information Retrieval System on the basi...Waqas Tariq
In this paper information retrieval system for local databases are discussed. The approach is to search the web both semantically and syntactically. The proposal handles the search queries related to the user who is interested in the focused results regarding a product with some specific characteristics. The objective of the work will be to find and retrieve the accurate information from the available information warehouse which contains related data having common keywords. This information retrieval system can eventually be used for accessing the internet also. Accuracy in information retrieval that is achieving both high precision and recall is difficult. So both semantic and syntactic search engine are compared for information retrieval using two parameters i.e. precision and recall.
Decision Support for E-Governance: A Text Mining ApproachIJMIT JOURNAL
Information and communication technology has the capability to improve the process by which governments involve citizens in formulating public policy and public projects. Even though much of government regulations may now be in digital form (and often available online), due to their complexity and diversity, identifying the ones relevant to a particular context is a non-trivial task. Similarly, with the advent of a number of electronic online forums, social networking sites and blogs, the opportunity of gathering citizens’ petitions and stakeholders’ views on government policy and proposals has increased greatly, but the volume and the complexity of analyzing unstructured data makes this difficult. On the other hand, text mining has come a long way from simple keyword search, and matured into a discipline capable of dealing with much more complex tasks. In this paper we discuss how text-mining techniques can help in retrieval of information and relationships from textual data sources, thereby assisting policy makers in discovering associations between policies and citizens’ opinions expressed in electronic public forums and blogs etc. We also present here, an integrated text mining based architecture for e-governance decision support along with a discussion on the Indian scenario.
Metadata is the information that is embedded
in a file whose contents are the explanation of the file. In the
handling of the main evidence with a metadata-based approach
is still a lot of manually in search for correlation related files to
uncover various cases of computer crime. However, when
correlated files are in separate locations (folders) and the
number of files will certainly be a formidable challenge for
forensic investigators in analyzing the evidence. In this study,
we will build a prototype analysis using a metadata-based
approach to analyze the correlation of the main proof file with
the associated file or deemed relevant in the context of the
investigation automatically based on the metadata parameters
of Author, Size, File Type and Date. In this research, the
related analysis read the characteristics of metadata file that is
file type Jpg, Docx, Pdf, Mp3 and Mp4 and analysis of digital
evidence correlation by using specified parameters, so it can
multiply the findings of evidence and facilitate analysis of
digital evidence. In this research, the result of correlation
analysis of digital evidence found that using parameter of
Author, Size, File Type and Date found less correlated file
while using parameter without Size and File Type found more
correlated file because of various extension and file size.
Classification-based Retrieval Methods to Enhance Information Discovery on th...IJMIT JOURNAL
The widespread adoption of the World-Wide Web (the Web) has created challenges both for society as a whole and for the technology used to build and maintain the Web. The ongoing struggle of information retrieval systems is to wade through this vast pile of data and satisfy users by presenting them with information that most adequately it’s their needs. On a societal level, the Web is expanding faster than we can comprehend its implications or develop rules for its use. The ubiquitous use of the Web has raised important social concerns in the areas of privacy, censorship, and access to information. On a technical level, the novelty of the Web and the pace of its growth have created challenges not only in the development of new applications that realize the power of the Web, but also in the technology needed to scale applications to accommodate the resulting large data sets and heavy loads. This thesis presents searching algorithms and hierarchical classification techniques for increasing a search service's understanding of web queries. Existing search services rely solely on a query's occurrence in the document collection to locate relevant documents. They typically do not perform any task or topic-based analysis of queries using other available resources, and do not leverage changes in user query patterns over time. Provided within are a set of techniques and metrics for performing temporal analysis on query logs. Our log analyses are shown to be reasonable and informative, and can be used to detect changing trends and patterns in the query stream, thus providing valuable data to a search service.
Enhanced Performance of Search Engine with Multitype Feature Co-Selection of ...IJASCSE
Information world meet many confronts nowadays and one such, is data retrieval from a multidimensional and heterogeneous data set. Han & et al carried out a trail for the mentioned challenge. A novel feature co-selection for web document clustering is proposed by them, which is called Multitype Features Co-selection for Clustering (MFCC). MFCC uses intermediate clustering results in one type of feature space to help the selection in other types of feature spaces. It reduces effectively of the noise introduced by “pseudoclass” and further improves clustering performance. This efficiency also can be used in data retrieval, by implementing the MFCC algorithm in ranking algorithm of Search Engine technique. The proposed work is to apply the MFCC algorithm in search engine architecture. Such that the information retrieves from the dataset is retrieved effectively and shows the relevant retrieval.
Web personalization using clustering of web usage dataijfcstjournal
The exponential growth in the number and the complexity of information resources and services on the Web
has made log data an indispensable resource to characterize the users for Web-based environment. It
creates information of related web data in the form of hierarchy structure through approximation. This
hierarchy structure can be used as the input for a variety of data mining tasks such as clustering,
association rule mining, sequence mining etc.
In this paper, we present an approach for personalizing web user environment dynamically when he
interacting with web by clustering of web usage data using concept hierarchy. The system is inferred from
the web server’s access logs by means of data and web usage mining techniques to extract the information
about users. The extracted knowledge is used for the purpose of offering a personalized view of the
services to users.
Chapter 1: Introduction to Information Storage and Retrievalcaptainmactavish1996
Course material for 3rd year Information Technology students. Information Storage and Retrieval Course. Chapter 1: Introduction to Information storage and retrieval
Text Mining is an Important part of data mining and it is used nowadays on a large scale. This mining technique is used to find patterns in text data collected from many online sources , and to gain some interestings insights from the patterns observed. Since text is basically everywhere on the internet, it becomes quite difficult to get the data in structured format, which is why text mining plays a huge role. It uses NLP(Natural Language Processing Techniques) to automate the text mining and this concept is used in Machine Learning.
INTELLIGENT INFORMATION RETRIEVAL WITHIN DIGITAL LIBRARY USING DOMAIN ONTOLOGYcscpconf
A digital library is a type of information retrieval (IR) system. The existing information retrieval
methodologies generally have problems on keyword-searching. We proposed a model to solve
the problem by using concept-based approach (ontology) and metadata case base. This model
consists of identifying domain concepts in user’s query and applying expansion to them. The
system aims at contributing to an improved relevance of results retrieved from digital libraries
by proposing a conceptual query expansion for intelligent concept-based retrieval. We need to
import the concept of ontology, making use of its advantage of abundant semantics and
standard concept. Domain specific ontology can be used to improve information retrieval from
traditional level based on keyword to the lay based on knowledge (or concept) and change the
process of retrieval from traditional keyword matching to semantics matching. One approach is
query expansion techniques using domain ontology and the other would be introducing a case
based similarity measure for metadata information retrieval using Case Based Reasoning
(CBR) approach. Results show improvements over classic method, query expansion using
general purpose ontology and a number of other approaches.
An information storage and retrieval system (ISRS) is a network with a built-in user interface that facilitates the creation, searching, and modification of stored data.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Mam assign
1. INTRODUCTION
The Information Retrieval System was coined by Calvin Mooers in
1952. These information retrieval systems were, truly speaking, document
retrieval system, since they were designed to retrieve information.
Information retrieval deals with storage, organization and access to text, as
well as multimedia information resources.
Information Retrieval is a process of searching some collection of
documents, using the term document in its widest sense, in order to
identify those documents which deal with a particular subject. Any system
that is designed to facilitate this literature searching may legitimately be
called an information retrieval system.
Information retrieval systems originally meant text retrieval systems, since
they were dealing with textual documents, modern information retrieval
systems deal with multimedia information comprising text, audio, images
and video. While many features of conventional text retrieval system are
equally applicable to multimedia information retrieval, the specific nature
of audio, image and video information have called for the development of
many new tools and techniques for information retrieval. Modern
information retrieval deals with storage, organization and access to text, as
well as multimedia information resources.
Definitions
According to Science and Technology Dictionary , information retrieval is
the technique and process of searching, recovering, and interpreting
information from large amounts of stored data.
Britannica Concise Encyclopedia says information retrieval is recovery of
information, especially in a database stored in a computer.
The concept of information retrieval is broad and often employed in an
imprecise meaning. It is used to denote systems designed to provide users
or a group of users with information.
2. The concept of information retrieval presupposes that there are some documents
or records containing information that have been organized in an order suitable
for easy retrieval. The documents or records we are concerned with contain
bibliographic information which is quite different from other kinds of information
or data. We may take a simple example. If we have a database of information
pertaining to an office, or a supermarket, all we have are the different kinds of
records and related facts, like names of employees, their positions, salary, and so
on, or in the case of a supermarket, names of different items, prices, quantity,
and so on. The main objective of a bibliographic information retrieval system,
however, is to retrieve the information-either the actual information or the
documents containing the information that fully or partially match the user’s
query. The database may contain abstracts or full texts of document, like
newspaper articles, handbooks, dictionaries, encyclopedias, legal documents,
statistics,etc., as well as audio, images, and video information.
An information retrieval system thus has three major components- the
document subsystem, the users subsystem , and the searching/retrieval
subsystem. These divisions are quite broad and each one is designed to
serve one or more functions, such as:
Analysis of documents and organization of information(creation of a
document database)
Analysis of user’s queries, preparation of a strategy to search the
database
Actual searching or matching of users queries with the database, and
finally
Retrieval of items that fully or partially match the search statement.
PURPOSE OF INFORMATION RETRIEVAL SYSTEM
An information retrieval system is designed to retrieve the documents
or information required by the user community. It should make the right
information available to the right user. Thus, an information retrieval system aims
3. at collecting and organizing information in one or more subject areas in order to
provide it the user as soon asked for. Belkin presents the following situation
which clearly reflects the purpose of information retrieval systems:
A writer presents as set of ideas in a document using a set of
concepts
Somewhere there will be some users who require the ideas but may
not be able to identify those. In other words, there will be some
persons who lack the ideas put forward by the author in his/her
work.
Information retrieval system serve to match the writers ideas
expressed in the document with the user requirements or demand
for those.
Thus, an information retrieval system serves as a bridge between the
world of creators or generators of information and the users of that
information.
Components of information retrieval system
An information retrieval system there are the documents or sources of
information and on the other there are the user’s queries. These two
sides are linked through a series of tasks. Lancaster mentions that an
information retrieval system comprises six major subsystems:
The document subsystem
The indexing subsystem
The vocabulary subsystem
The searching subsystem
The ser-system interfece,and
The matching subsystem
4. The broad outline of an information retrieval system
Subject or content analysis includes the tasks related to the analysis,
organization and storage of information. The process of search and retrieval
includes the tasks of analyzing user’s queries, creation of a search formula, the
actual searching, and retrieval of information. The major emphasis of this book is
laid on these two areas. Researchers in the information retrieval world are
engaged in developing suitable methodologies for both sets of operations.
Developments in the technological world, especially in computer and
communication technology, have provided an additional impectus to the
development of information retrieval systems. Researchers who are working on
the storage side of the information retrieval system are engaged in designing
Information
sources
Analysis and
Representation
Organized
Information
Retrieved
Information
Matching
Users Query Analysis Analyzed Queries
5. sophisticated methods for identification and representation of the various
bibliographic elements essential for documents, automatic content analysis, and
text processing, and so on. On the other hand, researchers working on the
retrieval side are attempting to develop sophisticated searching techniques, user
interfaces, and various techniques for producing output for local as well as
remote user.
Kinds of information retrieval systems
Two broad categories of information retrieval system can be identified: in-
house and online. In-house and online. In- house information retrieval systems
are set up by a particular library or information centre to serve mainly the users
within the organization. One particular type of in-house database is the library
catalogue. Online public access catalogues (OPACs) provide facilities for library
users to carry out online catalogue searches, and then to check the availability of
the item required.
By online information retrieval system we mean those that have been
designed to provide access to remote databases to a variety of users. Such
services are available mostly on a commercial basis, and there are a number of
vendors that handle this sort of service. With the development of optical storage
technology another type of information retrieval system appeared on CD-ROM.
Information retrieval systems based on CD-ROM technology are available mostly
on a commercial basis, though there have been some free and in-house
developments too. Basic techniques for search and retrieval of information from
the in-house or CD-ROM and online information retrieval systems are more or
less the same, except that the online system is linked to users at a distance
through the electronic communication network.
Recent developments in computer and communication technologies have
widened the scope of online information retrieval system. The Internet and World
Wide Web have made information available for use by anyone virtually anywhere
with access to the appropriate equipment. This has led to the concept of a digital
global library system where information can be generated and made available in
electronic form on the Web for use by any user from any corner of the world. This
6. of course involves a number of technical and management issues that need to be
resolved in order to make the global digit library concept a reality.
Functions of information retrieval system
An information retrieval system deals with various sources of information
on the one hand and user’s requirements on the other. It must:
Analyze the contents of the sources of information as well as the
user’s queries, and then
Match these to retrieve those items that are relevant
The major functions of an information retrieval system can be listed as
follows:
To identify the information(sources) relevant to the areas of interest of
the target users community
To analyze the contents of the sources(documents)
To represent the contents of the analyzed sources in a way that will be
suitable for matching user’s queries
To analyze user’s queries and to represent them in a form that will be
suitable for matching with the database
To match the search statement with the stored database
To retrieve the information that is relevant, and
To make necessary adjustments in the system based on feedback form
the users.
8. Features of an information retrieval system
Liston and Schoene suggest that an effective information retrieval system
must have provisions for:
Prompt dissemination of information
Filtering of information
The right amount of information at the right time
Active switching of information
Receiving information in an economical way
Browsing
Getting information in an economical way
Current literature
Access to other information systems
Interpersonal communications, and
Personalized help.
Conclusion
An information retrieval process begins when a user enters a query into the
system. Queries are formal statements of information needs, for example search
strings in web search engines. In information retrieval a query does not uniquely
identify a single object in the collection. Instead, several objects may match the
query, perhaps with different degrees of relevancy.
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.
Reference
www.information retrieval.com