Information Seeking, Information Retrieval: Philosophical Points
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Basic Concepts in Information Retrieval
1 Basic concepts of information retrieval systems Introduction The term ‘information retrieval’ was coined in 1952 and gained popularity in the research community from 1961 onwards.1 At that time the organizing function of information retrieval was seen as a major advance in libraries that were no longer just storehouses of books, but also places where the information they hold is catalogued and indexed.2 Subsequently, with the introduction of computers in information handling, there appeared a number of databases containing bibliographic details of documents, often married with abstracts, keywords, and so on, and consequently the concept of information retrieval came to mean the retrieval of bibliographic information from stored document databases. Information retrieval is concerned with all the activities related to the organization of, processing of, and access to, information of all forms and formats. An information retrieval system allows people to communicate with an information system or service in order to find information – text, graphic images, sound recordings or video that meet their specific needs. Thus the objective of an information retrieval system is to enable users to find relevant information from an organized collection of documents. In fact, most information retrieval systems are, truly speaking, document retrieval systems, since they are designed to retrieve information about the existence (or non-existence) of documents relevant to a user query. Lancaster3 comments that an information retrieval system does not inform (change the knowledge of) the user on the subject of their enquiry; it merely informs them of the existence (or non-existence) and whereabouts of documents relating to their request. -
Everyday Life Information Seeking
Everyday Life Information Seeking Reijo Savolainen Department of Information Studies and Interactive Media, University of Tampere, Tampere, Finland Folksonomies Ethiopia– Abstract Information seeking may be analyzed in two major contexts: job-related and nonwork. The present entry concentrates on nonwork information seeking, more properly called everyday life information seeking (ELIS). Typically, ELIS studies discuss the ways in which people access and use various information sources to meet information needs in areas such as health, consumption, and leisure. The entry specifies the concept of ELIS and characterizes the major ELIS models. They include the Sense-Making approach (Dervin), the Small world theory (Chatman), the ecological model of ELIS (Williamson), ELIS in the context of way of life (Savolainen), the model of information practices (McKenzie), and the concept of information grounds (Fisher). ELIS practices tend to draw on the habitualized use of a limited number of sources which have been found useful in previous use contexts. Since the late 1990s, the Internet has increasingly affected the ELIS practices by providing easily accessible sources. Even though the popularity of the networked sources has grown rapidly they will complement, rather than replace, more traditional sources and channels. INTRODUCTION THE CONCEPT OF ELIS Information seeking is a major constituent of information Thus far, a rich variety of themes have been explored in behavior or information practices, that is, the entirety of ELIS studies. They have focused on people belonging to ways in which people seek, use, and share information in diverse groups such as the following: different contexts.[1,2] Information seeking may be ana- lyzed in two major contexts: job-related and nonwork. -
Inst Xxx: Information User Needs & Assessment
INST408A_Consumer_Health_Informatics_Syllabus_Fall2019_StJean&Jardine_Final INST 408A-0101 Special Topics in Information Science: Consumer Health Informatics College of Information Studies, University of Maryland Mondays, 2:00 – 4:45 PM (Hornbake Library, North Wing, Room 0302H) Fall 2019 Co-Instructors: Beth St. Jean, Associate Professor Fiona Jardine, Doctoral Candidate Hornbake Building, Room 4117K Hornbake Building, Room 4105 301-405-6573 301-602-3936 [email protected] [email protected] Office Hours: Beth St. Jean: Mondays, 5:00 to 6:00 PM, or by appointment. Fiona Jardine: Fridays 12:00 to 1:00 PM, or by appointment. Our Liaison Librarian: Rachel Gammons, Head of Teaching and Learning Services, 4100C McKeldin Library, [email protected], 301-405-9120. [Research Guide: https://lib.guides.umd.edu/information_studies] Catalog Description [Prerequisite: INST 201 (Introduction to Information Science)] In this course, we will investigate the fields of Consumer Health Informatics and Information Behavior, focusing most heavily on their intersection – Consumer Health Information Behavior. We will explore people’s health-related information needs and whether, how, and why people seek out and use (or do not seek out and use) health information and the types of health information they find useful. We will also cover the important and interrelated topics of information avoidance, health behaviors, health literacy, digital health literacy, doctor-patient communication, and patient-to-patient communication through support groups and online communities. Throughout the course, we will also focus on the important concept of health justice – an ideal state in which everyone has an adequate and equitable capability to be healthy. We will identify populations that frequently experience social injustice and explore the information-related causes and broader consequences of the health inequities members of these populations tend to face. -
Study of Information Seeking Behavior and Library Use Pattern of Researchers in the Banasthali University
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Library Philosophy and Practice (e-journal) Libraries at University of Nebraska-Lincoln March 2013 Study of Information Seeking Behavior and Library Use Pattern of Researchers in the Banasthali University A.K. Pareek Banasthali University, [email protected] Madan S. Rana Assam University, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/libphilprac Part of the Library and Information Science Commons Pareek, A.K. and Rana, Madan S., "Study of Information Seeking Behavior and Library Use Pattern of Researchers in the Banasthali University" (2013). Library Philosophy and Practice (e-journal). 887. https://digitalcommons.unl.edu/libphilprac/887 Study of Information Seeking Behavior and Library Use Pattern of Researchers in the Banasthali University A.K.Pareek* Madan S. Rana** Abstract This study was undertaken to determine the information seeking behavior and library use by research scholars at the Banasthali University. The overall purpose of the study was to determine what their information requirements and also determine their awareness of library services available to them. The study collected data on the information requirements of researchers. Data were gathered from 100 researchers out of 150 through open and closed questionnaire. Findings indicate that guidance in the use of library resources and services is necessary to help researchers meet some of their information requirements. Keywords: Information seeking behavior; Library resources; e-resources; Inter-Library Loan (ILL); Documentary delivery. Introduction In library and information science research is a substantial body of work addressing information-related behavior, including information needs, information seeking and use of information resources. -
The Seven Ages of Information Retrieval
International Federation of Library Associations and Institutions UNIVERSAL DATAFLOW AND TELECOMMUNICATIONS CORE PROGRAMME OCCASIONAL PAPER 5 THE SEVEN AGES OF INFORMATION RETRIEVAL Michael Lesk Bellcore March, 1996 International Federation of Library Associations and Institutions UNIVERSAL DATAFLOW AND TELECOMMUNICATIONS CORE PROGRAMME The IFLA Core Programme on Universal Dataflow and Telecommunications (UDT) seeks to facilitate the international and national exchange of electronic data by providing the library community with pragmatic approaches to resource sharing. The programme monitors and promotes the use of relevant standards, promotes the use of relevant technologies and monitors relevant policy issues in an effort to overcome barriers to the electronic transfer of data in library fields. CONTACT INFORMATION Mailing Address: IFLA International Office for UDT c/o National Library of Canada 395 Wellington Street Ottawa, CANADA K1A 0N4 UDT Staff Contacts: Leigh Swain, Director Email: [email protected] Phone: (819) 994-6833 or Louise Lantaigne, Administration Officer Email: [email protected] Phone: (819) 994-6963 Fax: (819) 994-6835 Email: [email protected] URL: http://www.ifla.org/udt/ Occasional papers are available electronically at: http://www.ifla.org/udt/op/ UDT Occasional Papers # 5 Universal Dataflow and Telecommunications Core Programme International Federation of Library Associations and Institutions The Seven Ages of Information Retrieval Michael Lesk Bellcore [email protected] March, 1996 ABSTRACT analysis. This dates to a memo by Warren Weaver in 1949 [Weaver 1955] thinking about the success of Vannevar Bush's 1945 article set a goal of fast access computers in cryptography during the war, and to the contents of the world's libraries which looks suggesting that they could translate languages. -
Information Retrieval (Text Categorization)
Information Retrieval (Text Categorization) Fabio Aiolli http://www.math.unipd.it/~aiolli Dipartimento di Matematica Pura ed Applicata Università di Padova Anno Accademico 2008/2009 Dip. di Matematica F. Aiolli - Information Retrieval 1 Pura ed Applicata 2008/2009 Text Categorization Text categorization (TC - aka text classification) is the task of buiding text classifiers, i.e. sofware systems that classify documents from a domain D into a given, fixed set C = {c 1,…,c m} of categories (aka classes or labels) TC is an approximation task , in that we assume the existence of an ‘oracle’, a target function that specifies how docs ought to be classified. Since this oracle is unknown , the task consists in building a system that ‘approximates’ it Dip. di Matematica F. Aiolli - Information Retrieval 2 Pura ed Applicata 2008/2009 Text Categorization We will assume that categories are symbolic labels; in particular, the text constituting the label is not significant. No additional knowledge of category ‘meaning’ is available to help building the classifier The attribution of documents to categories should be realized on the basis of the content of the documents. Given that this is an inherently subjective notion, the membership of a document in a category cannot be determined with certainty Dip. di Matematica F. Aiolli - Information Retrieval 3 Pura ed Applicata 2008/2009 Single-label vs Multi-label TC TC comes in two different variants: Single-label TC (SL) when exactly one category should be assigned to a document The target function in the form f : D → C should be approximated by means of a classifier f’ : D → C Multi-label TC (ML) when any number {0,…,m} of categories can be assigned to each document The target function in the form f : D → P(C) should be approximated by means of a classifier f’ : D → P(C) We will often indicate a target function with the alternative notation f : D × C → {-1,+1} . -
Information Retrieval System: Concept and Scope MODULE - 5B INFORMATION RETRIEVAL SYSTEM
Information Retrieval System: Concept and Scope MODULE - 5B INFORMATION RETRIEVAL SYSTEM 15 Notes INFORMATION RETRIEVAL SYSTEM: CONCEPT AND SCOPE 15.1 INTRODUCTION Information is communicated or received knowledge concerning a particular fact or circumstance. Retrieval refers to searching through stored information to find information relevant to the task at hand. In view of this, information retrieval (IR) deals with the representation, storage, organization of/and access to information items. Here, types of information items include documents, Web pages, online catalogues, structured records, multimedia objects, etc. Chief goals of the IR are indexing text and searching for useful documents in a collection. Libraries were among the first institutions to adopt IR systems for retrieving information. In this lesson, you will be introduced to the importance, definitions and objectives of information retrieval. You will also study in detail the concept of subject approach to information, process of information retrieval, and indexing languages. 15.2 OBJECTIVES After studying this lesson, you will be able to: define information retrieval; understand the importance and need of information retrieval system; explain the concept of subject approach to information; LIBRARY AND INFORMATION SCIENCE 321 MODULE - 5B Information Retrieval System: Concept and Scope INFORMATION RETRIEVAL SYSTEM illustrate the process of information retrieval; and differentiate between natural, free and controlled indexing languages. 15.3 INFORMATION RETRIEVAL (IR) Notes The term ‘information retrieval’ was coined by Calvin Mooers in 1950. It gained popularity in the research community from 1961 onwards, when computers were introduced for information handling. The term information retrieval was then used to mean retrieval of bibliographic information from stored document databases. -
Understanding Information-Seeking Behaviour of Undergraduate Extension Program Students in Faculty of Administrative Science, Universitas Indonesia
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Library Philosophy and Practice (e-journal) Libraries at University of Nebraska-Lincoln Winter 2-1-2021 Understanding Information-Seeking Behaviour of Undergraduate Extension Program Students in Faculty of Administrative Science, Universitas Indonesia Indah Perdana Kusuma Universitas Indonesia, [email protected] Taufik Asmiyanto Universitas Indonesia, [email protected] Rahmi Rahmi Universitas Indonesia, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/libphilprac Part of the Library and Information Science Commons Kusuma, Indah Perdana; Asmiyanto, Taufik; and Rahmi, Rahmi, "Understanding Information-Seeking Behaviour of Undergraduate Extension Program Students in Faculty of Administrative Science, Universitas Indonesia" (2021). Library Philosophy and Practice (e-journal). 5060. https://digitalcommons.unl.edu/libphilprac/5060 Understanding Information-Seeking Behaviour of Undergraduate Extension Program Students in Faculty of Administrative Science, Universitas Indonesia Indah Perdana Kusuma1, Taufik Asmiyanto2, and Rahmi3 1 Undergraduate Student (graduated in August 2020), Department of Library and Information Science, Faculty of Humanities, Universitas Indonesia, Depok, 16424, Indonesia [email protected] 2 Corresponding author, 2,3 Lecturer in Department of Library and Information Science, Faculty of Humanities, Universitas Indonesia, Depok, 16424, Indonesia [email protected]; [email protected] Abstract: The information -
A Philosophical Wish List for Research in Music Information Retrieval Cynthia M
A Philosophical Wish List for Research in Music Information Retrieval Cynthia M. Grund Institute of Philosophy, Education and the Study of Religions - Philosophy University of Southern Denmark, Odense [email protected] Abstract what might otherwise seem utterly intractable questions. Within a framework provided by the traditional trio What insights could MIR-research provide into the consisting of metaphysics, epistemology and ethics, a first great questions of philosophy? The answer lies in the stab is made at a wish list for MIR-research from a particular facility which the tools of MIR possess for philosophical point of view. Since the tools of MIR are dealing with language as a sonic phenomenon, thus 1 equipped to study language and its use from a purely sonic providing yet another revolution in the linguistic turn. A standpoint, MIR research could result in another revealing search through the reams of literature produced regarding revolution within the linguistic turn in philosophy. the role of language in philosophical endeavor reveals that the language framework is virtually always a written one. Keywords: Philosophy and MIR, language as spoken, Little or no attention has been paid to the mechanisms at memory work in thinking, learning and communicating in a context 2 1. Introduction and Brief Setting of the Stage which is virtually of an exclusively oral, sonic. Since the overwhelming majority of time during which our thinking, Philosophy wrestles with questions regarding learning and communicative skills developed was metaphysics, -
An Architecture for Information Retrieval Agents* Craig A
From: AAAI Technical Report SS-94-03. Compilation copyright © 1994, AAAI (www.aaai.org). All rights reserved. An Architecture for Information Retrieval Agents* Craig A. Knoblock and Yigal Arens Information Sciences Institute University of Southern California 4676 Admiralty Way Marina del Rey, CA 90292, USA {KNOBLOCK,ARENS}QISI.ED Abstract sources that are available to it. Given an informa- tion request, an agent identifies an appropriate set of With the vast number of information resources information sources, generates a plan to retrieve and available today, a critical problem is howto lo- process the data, uses knowledge about the data to re- cate, retrieve and process information. It would formulate the plan, and then executes it. This paper be impractical to build a single unified system that describes our approach to the issues of representation, combines all of these information resources. A communication, problem solving, and learning, and de- more promising approach is to build specialized scribes how this approach supports multiple, collabo- information retrieval agents that provide access rating information retrieval agents. to a subset of the information resources and can send requests to other information retrieval agents Representing the Knowledge of an when needed. In this paper we present an archi- tecture for building such agents that addresses the Agent issues of representation, communication, problem Each information agent is specialized to a particular solving, and learning. Wealso describe how this area of expertise. This provides a modular organiza- architecture supports agents that are modular, ex- tion of the vast numberof information sources and pro- tensible, flexible and efficient, vides a clear delineation of the types of queries each agent can handle. -
Semantic Information Retrieval Based on Wikipedia Taxonomy
International Journal of Computer Applications Technology and Research Volume 2– Issue 1, 77-80, 2013, ISSN: 2319–8656 Semantic Information Retrieval based on Wikipedia Taxonomy May Sabai Han University of Technology Yatanarpon Cyber City Myanmar Abstract: Information retrieval is used to find a subset of relevant documents against a set of documents. Determining semantic similarity between two terms is a crucial problem in Web Mining for such applications as information retrieval systems and recommender systems. Semantic similarity refers to the sameness of two terms based on sameness of their meaning or their semantic contents. Recently many techniques have introduced measuring semantic similarity using Wikipedia, a free online encyclopedia. In this paper, a new technique of measuring semantic similarity is proposed. The proposed method uses Wikipedia as an ontology and spreading activation strategy to compute semantic similarity. The utility of the proposed system is evaluated by using the taxonomy of Wikipedia categories. Keywords: information retrieval; semantic similarity; spreading activation strategy; wikipedia taxonomy; wikipedia categories 1. INTRODUCTION fashion than a search engine and with more coverage than WordNet. And Wikipedia articles have been categorized by Information in WWW are scattered and diverse in nature. So, providing a taxonomy, categories. This feature provides the users frequently fail to describe the information desired. hierarchical structure or network. Wikipedia also provides Traditional search techniques are constrained by keyword articles link graph. So many researches has recently used based matching techniques. Hence low precision and recall is Wikipedia as an ontology to measure semantic similarity. obtained [2]. Many natural language processing applications must estimate the semantic similarity of pairs of text We propose a method to use structured knowledge extracted fragments provided as input, e.g. -
Introduction to Information Retrieval
DRAFT! © April 1, 2009 Cambridge University Press. Feedback welcome. 1 1 Boolean retrieval The meaning of the term information retrieval can be very broad. Just getting a credit card out of your wallet so that you can type in the card number is a form of information retrieval. However, as an academic field of study, INFORMATION information retrieval might be defined thus: RETRIEVAL Information retrieval (IR) is finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within large collections (usually stored on computers). As defined in this way, information retrieval used to be an activity that only a few people engaged in: reference librarians, paralegals, and similar pro- fessional searchers. Now the world has changed, and hundreds of millions of people engage in information retrieval every day when they use a web search engine or search their email.1 Information retrieval is fast becoming the dominant form of information access, overtaking traditional database- style searching (the sort that is going on when a clerk says to you: “I’m sorry, I can only look up your order if you can give me your Order ID”). IR can also cover other kinds of data and information problems beyond that specified in the core definition above. The term “unstructured data” refers to data which does not have clear, semantically overt, easy-for-a-computer structure. It is the opposite of structured data, the canonical example of which is a relational database, of the sort companies usually use to main- tain product inventories and personnel records.