Nicholas J. Belkin | |
---|---|
Born | 1942 |
Nationality | American |
Known for | Anomalous State of Knowledge for Information Retrieval |
Awards | Gerard Salton Award (2015) |
Scientific career | |
Fields | Computer Science |
Institutions | Rutgers University |
Nicholas J. Belkin is a professor at the School of Communication and Information at Rutgers University. Among the main themes of his research are digital libraries; information-seeking behaviors; and interaction between humans and information retrieval systems. Belkin is best known for his work on human-centered Information Retrieval and the hypothesis of Anomalous State of Knowledge (ASK). Belkin realized that in many cases, users of search systems are unable to precisely formulate what they need. They miss some vital knowledge to formulate their queries. In such cases it is more suitable to attempt to describe a user's anomalous state of knowledge than to ask the user to specify her/his need as a request to the system. [1] [2]
Belkin was the chair of SIGIR in 1995-99, and the president of American Society for Information Science and Technology in 2005. [3] In 2015, Belkin received the Gerard Salton Award. [4]
Nicholas Belkin studied Slavic Philology at the University of Washington, graduating in 1968. He graduated from the same college in Library Science 2 years later (1970), and read his doctoral thesis in 1977 in the University of London. He worked in the Information Science department of this university from 1975 to 1985. That year, he signed for the Faculty of Communication and Information at Rutgers University (USA).
He has been a visiting professor at Western Ontario University(Canada), Dhirubhai Ambani Institute of Information and Communication Technology (India) and Free University of Berlin. He has been a visiting researcher at the National University of Singapore in 1996. He has given more than 200 lectures around the world.
He has been president of Association for Computing Machinery SIGIR (Special Interest Group on Information Retrieval) during the period 1995-1999, and president of the American Society of Information Science and Technology (ASIST) in 2005.
Nicholas Belkin has served on numerous editorial boards of numerous scientific journals. Among the most prestigious are "Information Processing and Management" and "Information Retrieval".
Nicholas Belkin has approached information retrieval from the so-called cognitive models , that is, those focused on users who access document systems. Belkin approached his research from 3 basic lines:
In 1977, Belkin read his thesis where he developed a new theory of the concept documentary information . This would be a structure that would allow the user to transform his anomalous state of knowledge (Anomalous State of Knowledge or ASK), when the need for information is satisfied, producing an adequate connection between the two ends of the documentary process: the producer and the receiver or user.
For Belkin, the purpose towards which Documentation works is to make this effective communication possible, which would imply the study of documentary information in human and cognitive communication systems, the connection between this information and its producer, the connection between information and user, gives the idea of the requested information and the effectiveness between information and document and its transmission process.
Belkin concludes that the concept of documentary information is the combination of a cognitive communication system, a structural representation of knowledge, the implementation of the project via user when he recognizes the need for information (ASK9, the meaning of the text ( message) and the interest in solving the problem of information science. This theory has also been developed by Oddy and Brooks.
Nicholas Belkin proposed a novel cognitive model of information retrieval, referred to as 'episodic' . In this, Belkin defines a set of interactions that occur between the user and the system during the consultation to "conceptualize, label and transcribe the need for information, as well as make relevant judgments about one or more documents." The components would be the same as those used in the traditional model: navigation (browsing), query (querying), display, indexing, representation and matching.
This model pays very little attention to the structure of documents and their retrieval, because it focuses on the anomalous state of knowledge of the individual, how to represent it, how to retrieve it, so it is based on the storage, retrieval and interaction of the search strategy.
Nicholas Belkin has been awarded numerous times, obtaining in 2003 the Award of Merit , and the Gerard Salton Award in 2015.
Belkin has published numerous articles in the most prestigious magazines in the field of Information and Documentation, some awarded by the ASIST. He is also the author of the book: Interaction in Information Systems: A Review of Research from Document Retrieval to Knowledge- Based Systems (1985) co-authored with Alina Vickery.
Information retrieval (IR) in computing and information science is the task of identifying and retrieving information system resources that are relevant to an information need. The information need can be specified in the form of a search query. In the case of document retrieval, queries can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.
Information science is an academic field which is primarily concerned with analysis, collection, classification, manipulation, storage, retrieval, movement, dissemination, and protection of information. Practitioners within and outside the field study the application and the usage of knowledge in organizations in addition to the interaction between people, organizations, and any existing information systems with the aim of creating, replacing, improving, or understanding the information systems.
In information science and information retrieval, relevance denotes how well a retrieved document or set of documents meets the information need of the user. Relevance may include concerns such as timeliness, authority or novelty of the result.
Gerard A. "Gerry" Salton was a professor of Computer Science at Cornell University. Salton was perhaps the leading computer scientist working in the field of information retrieval during his time, and "the father of Information Retrieval". His group at Cornell developed the SMART Information Retrieval System, which he initiated when he was at Harvard. It was the very first system to use the now popular vector space model for Information Retrieval.
The SMART Information Retrieval System is an information retrieval system developed at Cornell University in the 1960s. Many important concepts in information retrieval were developed as part of research on the SMART system, including the vector space model, relevance feedback, and Rocchio classification.
The Gerard Salton Award is presented by the Association for Computing Machinery (ACM) Special Interest Group on Information Retrieval (SIGIR) every three years to an individual who has made "significant, sustained and continuing contributions to research in information retrieval". SIGIR also co-sponsors the Vannevar Bush Award, for the best paper at the Joint Conference on Digital Libraries.
Exploratory search is a specialization of information exploration which represents the activities carried out by searchers who are:
Relevance feedback is a feature of some information retrieval systems. The idea behind relevance feedback is to take the results that are initially returned from a given query, to gather user feedback, and to use information about whether or not those results are relevant to perform a new query. We can usefully distinguish between three types of feedback: explicit feedback, implicit feedback, and blind or "pseudo" feedback.
Query expansion (QE) is the process of reformulating a given query to improve retrieval performance in information retrieval operations, particularly in the context of query understanding. In the context of search engines, query expansion involves evaluating a user's input and expanding the search query to match additional documents. Query expansion involves techniques such as:
Human–computer information retrieval (HCIR) is the study and engineering of information retrieval techniques that bring human intelligence into the search process. It combines the fields of human-computer interaction (HCI) and information retrieval (IR) and creates systems that improve search by taking into account the human context, or through a multi-step search process that provides the opportunity for human feedback.
Knowledge retrieval seeks to return information in a structured form, consistent with human cognitive processes as opposed to simple lists of data items. It draws on a range of fields including epistemology, cognitive psychology, cognitive neuroscience, logic and inference, machine learning and knowledge discovery, linguistics, and information technology.
The following outline is provided as an overview of and topical guide to information science:
W. Bruce Croft is a distinguished professor of computer science at the University of Massachusetts Amherst whose work focuses on information retrieval. He is the founder of the Center for Intelligent Information Retrieval and served as the editor-in-chief of ACM Transactions on Information Systems from 1995 to 2002. He was also a member of the National Research Council Computer Science and Telecommunications Board from 2000 to 2003. Since 2015, he is the Dean of the College of Information and Computer Sciences at the University of Massachusetts Amherst. He was Chair of the UMass Amherst Computer Science Department from 2001 to 2007.
Cognitive models of information retrieval rest on the mix of areas such as cognitive science, human-computer interaction, information retrieval, and library science. They describe the relationship between a person's cognitive model of the information sought and the organization of this information in an information system. These models attempt to understand how a person is searching for information so that the database and the search of this database can be designed in such a way as to best serve the user. Information retrieval may incorporate multiple tasks and cognitive problems, particularly because different people may have different methods for attempting to find this information and expect the information to be in different forms. Cognitive models of information retrieval may be attempts at something as apparently prosaic as improving search results or may be something more complex, such as attempting to create a database which can be queried with natural language search.
Learning to rank or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. Training data may, for example, consist of lists of items with some partial order specified between items in each list. This order is typically induced by giving a numerical or ordinal score or a binary judgment for each item. The goal of constructing the ranking model is to rank new, unseen lists in a similar way to rankings in the training data.
Information behavior is a field of information science research that seeks to understand the way people search for and use information in various contexts. It can include information seeking and information retrieval, but it also aims to understand why people seek information and how they use it. The term 'information behavior' was coined by Thomas D. Wilson in 1982 and sparked controversy upon its introduction. The term has now been adopted and Wilson's model of information behavior is widely cited in information behavior literature. In 2000, Wilson defined information behavior as "the totality of human behavior in relation to sources and channels of information".
Jason Farradane, born Jason Lewkowitsch was a British librarian of Polish descent.
Vocabulary mismatch is a common phenomenon in the usage of natural languages, occurring when different people name the same thing or concept differently.
ChengXiang Zhai is a computer scientist. He is a Donald Biggar Willett Professor in Engineering in the Department of Computer Science at the University of Illinois at Urbana-Champaign.
The Award of Merit is bestowed by the Association for Information Science and Technology. It is an annual prize to an individual for a lifetime of achievement that recognizes sustained contributions to and/or achievements in the field of information science and/or the professions in which it is practiced. The Award of Merit was first given in 1964.
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