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In library and information science, the information search process (ISP) is a six-stage process of information seeking behavior. The ISP was first suggested by Carol Kuhlthau in 1991. It describes the thoughts, feelings and actions of the searcher, and is often used to describe students. [1]
During the first stage, initiation, the information seeker recognizes the need for new information to complete an assignment. [2] As they think more about the topic, they may discuss the topic with others and brainstorm the topic further. [3] This stage of the information seeking process is filled with feelings of apprehension and uncertainty.
In the second stage, selection, the individual begins to decide what topic will be investigated and how to proceed. [2] Some information retrieval may occur at this point, resulting in multiple rounds of query reformulation. [4] The uncertainty associated with the first stage often fades with the selection of a topic, and is replaced with a sense of optimism.
In the third stage, exploration, information on the topic is gathered and a new personal knowledge is created. [5] Students endeavor to locate new information and situate it within their previous understanding of the topic. [2] In this stage, feelings of anxiety may return if the information seeker finds inconsistent or incompatible information.
During the fourth stage, formulation, the information seeker starts to evaluate the information that has been gathered. At this point, a focused perspective begins to form and there is not as much confusion and uncertainty as in earlier stages. [5] Formulation is considered to be the most important stage of the process. [3] The information seeker will here formulate a personalized construction of the topic from the general information gathered in the exploration phase. [2]
During the fifth stage, collection, the information seeker knows what is needed to support the focus. Now presented with a clearly focused, personalized topic, the information seeker will experience greater interest, increased confidence, and more successful searching. [2] [6]
In the sixth and final stage, search closure, the individual has completed the information search. Now the information seeker will summarize and report on the information that was found through the process. The information seeker will experience a sense of relief and, depending on the fruits of their search, either satisfaction or disappointment. [2]
Information retrieval (IR) in computing and information science is the process of obtaining information system resources that are relevant to an information need from a collection of those resources. Searches 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.
PubMed is a free search engine accessing primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics. The United States National Library of Medicine (NLM) at the National Institutes of Health maintain the database as part of the Entrez system of information retrieval.
Curiosity is a quality related to inquisitive thinking such as exploration, investigation, and learning, evident by observation in humans and other animals. Curiosity is heavily associated with all aspects of human development, in which derives the process of learning and desire to acquire knowledge and skill.
Federated search retrieves information from a variety of sources via a search application built on top of one or more search engines. A user makes a single query request which is distributed to the search engines, databases or other query engines participating in the federation. The federated search then aggregates the results that are received from the search engines for presentation to the user. Federated search can be used to integrate disparate information resources within a single large organization ("enterprise") or for the entire web.
The uncertainty reduction theory, also known as initial interaction theory, developed in 1975 by Charles Berger and Richard Calabrese, is a communication theory from the post-positivist tradition. It is one of the few communication theories that specifically looks into the initial interaction between people prior to the actual communication process. The theory asserts the notion that, when interacting, people need information about the other party in order to reduce their uncertainty. In gaining this information people are able to predict the other's behavior and resulting actions, all of which according to the theory is crucial in the development of any relationship.
Exploratory search is a specialization of information exploration which represents the activities carried out by searchers who are:
Social search is a behavior of retrieving and searching on a social searching engine that mainly searches user-generated content such as news, videos and images related search queries on social media like Facebook, LinkedIn, Twitter, Instagram and Flickr. It is an enhanced version of web search that combines traditional algorithms. The idea behind social search is that instead of ranking search results purely based on semantic relevance between a query and the results, a social search system also takes into account social relationships between the results and the searcher. The social relationships could be in various forms. For example, in LinkedIn people search engine, the social relationships include social connections between searcher and each result, whether or not they are in the same industries, work for the same companies, belong the same social groups, and go the same schools, etc.
Carol Collier Kuhlthau is a retired American educator, researcher, and international speaker on learning in school libraries, information literacy, and information seeking behavior.
Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Information seeking is related to, but different from, information retrieval (IR).
Geographic information retrieval (GIR) or geographical information retrieval systems are search tools for searching the Web, enterprise documents, and mobile local search that combine traditional text-based queries with location querying, such as a map or placenames. Like traditional information retrieval systems, GIR systems index text and information from structured and unstructured documents, and also augment those indices with geographic information. The development and engineering of GIR systems aims to build systems that can reliably answer queries that include a geographic dimension, such as "What wars were fought in Greece?" or "restaurants in Beirut". Semantic similarity and word-sense disambiguation are important components of GIR. To identify place names, GIR systems often rely on natural language processing or other metadata to associate text documents with locations. Such georeferencing, geotagging, and geoparsing tools often need databases of location names, known as gazetteers.
A web query or web search query is a query that a user enters into a web search engine to satisfy their information needs. Web search queries are distinctive in that they are often plain text and boolean search directives are rarely used. They vary greatly from standard query languages, which are governed by strict syntax rules as command languages with keyword or positional parameters.
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.
A Web query topic classification/categorization is a problem in information science. The task is to assign a Web search query to one or more predefined categories, based on its topics. The importance of query classification is underscored by many services provided by Web search. A direct application is to provide better search result pages for users with interests of different categories. For example, the users issuing a Web query "apple" might expect to see Web pages related to the fruit apple, or they may prefer to see products or news related to the computer company. Online advertisement services can rely on the query classification results to promote different products more accurately. Search result pages can be grouped according to the categories predicted by a query classification algorithm. However, the computation of query classification is non-trivial. Different from the document classification tasks, queries submitted by Web search users are usually short and ambiguous; also the meanings of the queries are evolving over time. Therefore, query topic classification is much more difficult than traditional document classification tasks.
A concept search is an automated information retrieval method that is used to search electronically stored unstructured text for information that is conceptually similar to the information provided in a search query. In other words, the ideas expressed in the information retrieved in response to a concept search query are relevant to the ideas contained in the text of the query.
Collaborative search engines (CSE) are Web search engines and enterprise searches within company intranets that let users combine their efforts in information retrieval (IR) activities, share information resources collaboratively using knowledge tags, and allow experts to guide less experienced people through their searches. Collaboration partners do so by providing query terms, collective tagging, adding comments or opinions, rating search results, and links clicked of former (successful) IR activities to users having the same or a related information need.
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.
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 1981 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".
Collaborative information seeking (CIS) is a field of research that involves studying situations, motivations, and methods for people working in collaborative groups for information seeking projects, as well as building systems for supporting such activities. Such projects often involve information searching or information retrieval (IR), information gathering, and information sharing. Beyond that, CIS can extend to collaborative information synthesis and collaborative sense-making.
Personalized search refers to web search experiences that are tailored specifically to an individual's interests by incorporating information about the individual beyond the specific query provided. There are two general approaches to personalizing search results, involving modifying the user's query and re-ranking search results.