scholarly journals Applications of Cognitive Intelligence in the Information Retrieval Process and Associated Challenges

2021 ◽  
Vol 15 (1) ◽  
pp. 26-38
Author(s):  
Mamata Rath ◽  
Joel J. P. C. Rodrigues ◽  
George S. Oreku
Keyword(s):  
Information Retrieval ◽  
Relevant Information ◽  
Cognitive Models ◽  
Position Estimation ◽  
Retrieval Process ◽  
Dynamic Scenes ◽  
Cognitive Intelligence ◽  
Objective State ◽  
Technology Domain

Information retrieval refers to a noteworthy system of identifying relevant information and recovering it through specific procedures from stored system. These technique is used in many differentiated applications that deal with subjective intelligence. Applications based on information retrieval are identified with various issues, for example, in technology domain, the sudden size changes of the objectives as they approach the sensor. If not taken care of appropriately, the altered changes can present substantial issues in information affiliation and position estimation. Under such a system, the meaning of the objective state is the fundamental advance for programmed comprehension of dynamic scenes. This is the reason of requirement of cognitive models for information retrieval. The existent models move around the connection between data list terms and records.

Semantic Analysis Based Approach for Relevant Text Extraction Using Ontology

2017 ◽  
Vol 7 (4) ◽  
pp. 19-36 ◽  
Author(s):  
Poonam Chahal ◽  
Manjeet Singh ◽  
Suresh Kumar
Keyword(s):  
Information Retrieval ◽  
Semantic Information ◽  
Semantic Analysis ◽  
Similarity Index ◽  
Relevant Information ◽  
Retrieval Process ◽  
Maximum Information ◽  
Text Extraction ◽  
Novel Technique ◽  
Text Content

Semantic analysis computation is done by extracting the interrelated concepts used by an author in the text/content of document. The concepts and linking i.e. relationships that are available among the concepts are most relevant as they provide the maximum information related to the event or activity as described by an author in the document. The retrieved relevant information from the text helps in the construction of the summary of a large text present in the document. This summary can further be represented in form of ontology and utilized in various application areas of information retrieval process like crawling, indexing, ranking, etc. The constructed ontologies can be compared with each other for calculation of similarity index based on semantic analysis between any texts. This paper gives a novel technique for retrieving the relevant semantic information represented in the form of ontology for true semantic analysis of given text.

A distributional semantics-based information retrieval framework for online social networks

2021 ◽  
pp. 1-11
Author(s):  
V.S. Anoop ◽  
P. Deepak ◽  
S. Asharaf
Keyword(s):  
Social Networks ◽  
Information Retrieval ◽  
Online Social Networks ◽  
Latent Dirichlet Allocation ◽  
Relevant Information ◽  
Distributional Semantics ◽  
Scalable Algorithms ◽  
Mobile Platforms ◽  
Cancer Support ◽  
Efficient Extraction

Online social networks are considered to be one of the most disruptive platforms where people communicate with each other on any topic ranging from funny cat videos to cancer support. The widespread diffusion of mobile platforms such as smart-phones causes the number of messages shared in such platforms to grow heavily, thus more intelligent and scalable algorithms are needed for efficient extraction of useful information. This paper proposes a method for retrieving relevant information from social network messages using a distributional semantics-based framework powered by topic modeling. The proposed framework combines the Latent Dirichlet Allocation and distributional representation of phrases (Phrase2Vec) for effective information retrieval from online social networks. Extensive and systematic experiments on messages collected from Twitter (tweets) show this approach outperforms some state-of-the-art approaches in terms of precision and accuracy and better information retrieval is possible using the proposed method.

OP457 A Collaborative Horizon Scanning Alert For Disinvestment And Early Awareness

2020 ◽  
Vol 36 (S1) ◽  
pp. 10-10
Author(s):  
Vigdis Lauvrak ◽  
Kelly Farrah ◽  
Rosmin Esmail ◽  
Anna Lien Espeland ◽  
Elisabet Hafstad ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Interest Group ◽  
Pilot Project ◽  
Relevant Information ◽  
Horizon Scanning ◽  
Google Alerts ◽  
One Year ◽  
The One ◽  
New Research ◽  
Google Search

IntroductionIn 2019, the Norwegian Institute for Public Health and Canadian Agency for Drugs and Technologies in Health (CADTH) received support from HTAi to produce a quarterly current awareness alert for the HTAi Disinvestment and Early Awareness Interest Group in collaboration with the HTAi Information Retrieval Interest Group. The alert focuses on methods and topical issues, and broader forecasts of potentially disruptive technologies that may be of interest to those involved in horizon scanning and disinvestment initiatives in health technology assessment (HTA).MethodsInformation specialists at both agencies developed search strategies for disinvestment and for horizon scanning in PubMed and Google. The template for the alert was based on an e-newsletter developed by the Information Retrieval Interest Group. Information specialists and researchers reviewed the monthly (PubMed) and weekly (Google) search results and selected potentially relevant publications. Additional sources were also identified through regular HTA and horizon scanning work.ResultsAlerts are posted quarterly on the HTAi Interest Group website; members receive an email notice when new alerts are available. While the revised PubMed searches are identifying relevant information, Google alerts have been disappointing, and this search may need to be revised further or dropped. When the one-year pilot project ends, in Fall 2020, interest group members will be surveyed to see if the alerts were useful, and whether they have suggestions for improving them.ConclusionsCollaborating on this alert service reduces duplication of effort between agencies, and makes new research in horizon scanning and disinvestment more accessible to colleagues in other agencies working in these areas.

Open System for Indexing and Retrieving Multimedia Information

2013 ◽  
Author(s):  
Hanene Maghrebi ◽  
Amos David
Keyword(s):  
Information Retrieval ◽  
Multimedia Information ◽  
Open System ◽  
Large Volume ◽  
Retrieval System ◽  
Main Idea ◽  
Relevant Information ◽  
Information Retrieval System ◽  
Multimedia Content ◽  
Nous Proposons

Managing the increasing growth of multimedia content still poses some problems. The challenge is to propose relevant information to the users among the large volume of information available. The main idea that drives our approach is to provide an open information retrieval system, which can adapt its results to several…La gestion de l’information multimédia soulève encore quelques problèmes. Le défi est de pouvoir proposer à l’utilisateur des informations pertinentes parmi la quantité d’information qui ne cesse de s’accroître. Dans cette lignée, nous proposons un système ouvert de recherche d’information capable d’adapter ses résultats aux différents… 

Databases in small specialized libraries

2002 ◽  
Vol 23 (2) ◽  
pp. 68-69
Author(s):  
Elna Schoeman ◽  
Jacqueline Kalley
Keyword(s):  
Information Retrieval ◽  
Relevant Information

This study of indexing in two small special libraries reveals the pitfalls encountered but also focuses on the satisfaction of being able to provide timely and relevant information retrieval through indexing.

Indexing and Abstracting as Tools for Information Retrieval in Digital Libraries

2018 ◽  
pp. 573-595
Author(s):  
Olaronke O. Fagbola
Keyword(s):  
Information Retrieval ◽  
Literature Review ◽  
Digital Libraries ◽  
Information Resource ◽  
Potential User ◽  
Retrieval Process ◽  
Road Signs ◽  
Retrieval Systems ◽  
Knowledge Organisation ◽  
Information Retrieval Systems

Indexing and abstracting are like Siamese twins in the information retrieval process. Indexing and abstracting are the two approaches to distilling information content into an abbreviated, but comprehensive representation of an information resource(s). They are knowledge organisation tools which usually provide detailed and accurate maps and road signs in the information superhighway. Digital libraries are characterised by an electronic stock of information which can be accessed via computers, and are extension and augmentations of physical libraries in digital forms. They are information retrieval systems (a device interposed between a potential user of information and the information itself) which provide opportunities to access and retrieve information that is often accessible for a variety of reasons. This chapter presents a literature review on indexing and abstracting, information retrieval process, digital libraries pointing out the importance of indexing and abstracting in the information retrieving process and then highlighting the roles played by indexing and abstracting as tools for information retrieval in digital libraries. The chapter posits that indexing and abstracting plays a significant role as information retrieval tools in digital libraries.

Cross-Lingual Information Retrieval

2005 ◽  
pp. 153-170 ◽  
Author(s):  
Christopher Yang ◽  
Kar W. Li
Keyword(s):  
Information Retrieval ◽  
Digital Library ◽  
Digital Libraries ◽  
World Wide ◽  
Relevant Information ◽  
Semantic Interoperability ◽  
Library Research ◽  
The World ◽  
Cross Lingual ◽  
Multiple Languages

Structural and semantic interoperability have been the focus of digital library research in the early 1990s. Many research works have been done on searching and retrieving objects across variations in protocols, formats, and disciplines. As the World Wide Web has become more popular in the last ten years, information is available in multiple languages in global digital libraries. Users are searching across the language boundary to identify the relevant information that may not be available in their own language. Cross-lingual semantic interoperability has become one of the focuses in digital library research in the late 1990s. In particular, research in cross-lingual information retrieval (CLIR) has been very active in recent conferences on information retrieval, digital libraries, knowledge management, and information systems. The major problem in CLIR is how to build the bridge between the representations of user queries and documents if they are of different languages.

Three-Dimensional Information Retrieval (3DIR)

2018 ◽  
pp. 1016-1029
Author(s):  
Peter Demian ◽  
Kirti Ruikar ◽  
Tarun Sahu ◽  
Anne Morris
Keyword(s):  
Information Retrieval ◽  
3D Visualization ◽  
Three Dimensional ◽  
Relevant Information ◽  
Tight Coupling ◽  
Care Needs ◽  
3D Objects ◽  
Topological Relationships ◽  
3D Geometry ◽  
Other Information

An increasing amount of information is packed into BIMs, with the 3D geometry serving as a central index leading to other information. The 3DIR project investigates information retrieval from such environments. Here, the 3D visualization can be exploited when formulating queries, computing the relevance of information items, or visualizing search results. The need for such a system was specified using workshops with end users. A prototype was built on a commercial BIM platform. Following an evaluation, the system was enhanced to exploit model topology. Relationships between 3D objects are used to widen the search, whereby relevant information items linked to a related 3D object (rather than linked directly to objects selected by the user) are still retrieved but ranked lower. An evaluation of the enhanced prototype demonstrates its effectiveness but highlights its added complexity. Care needs to be taken when exploiting topological relationships, but that a tight coupling between text-based retrieval and the 3D model is generally effective in information retrieval from BIMs.

Need of Intelligent Search in Dynamic Social Network

2018 ◽  
pp. 144-157
Author(s):  
Shailendra Kumar Sonkar ◽  
Vishal Bhatnagar ◽  
Rama Krishna Challa
Keyword(s):  
Information Retrieval ◽  
Social Network ◽  
Web Mining ◽  
Relevant Information ◽  
Future Research ◽  
Intelligent Search ◽  
Dynamic Social Network ◽  
The Social ◽  
Intelligent Information ◽  
Conference Papers

The user of dynamic social network does not require irrelevant and vast amount of information during a search. A need of an intelligent search is required to get the reduced, filtered and relevant information that is achieved using an intelligent information retrieval and web mining. In this paper, identification and description of facts related to needs of an intelligent search in dynamic social network has been done by the authors after the deep and thorough study conducted on several journal and conference papers that are scattered on different electronic databases globally. The usage of intelligent agent for effective information retrieval from the social network site is a very emerging area and it will help the users to find the relevant and concerned information quickly and efficiently. The findings of the authors will help researchers and scholars who are already working in this area to get the relevant information in the direction of future research.

State-of-the-Art Information Retrieval Tools for Biological Resources

2018 ◽  
pp. 77-96
Author(s):  
Shashi Bhushan Lal ◽  
Anu Sharma ◽  
Krishna Kumar Chaturvedi ◽  
Mohammad Samir Farooqi ◽  
Sanjeev Kumar ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Statistical Analysis ◽  
Relevant Information ◽  
Ease Of Use ◽  
Video Data ◽  
Biological Databases ◽  
Biological Resources ◽  
Sequencing Technologies ◽  
Scientific Experiments ◽  
Insight Into

With the advancements in sequencing technologies, there is an exponential growth in the availability of the biological databases. Biological databases consist of information and knowledge collected from scientific experiments, published literature and statistical analysis of text, numerical, image and video data. These databases are widely spread across the globe and are being maintained by many organizations. A number of tools have been developed to retrieve the information from these databases. Most of these tools are available on web but are scattered. So, finding a relevant information is a very difficult, and tedious task for the researchers. Moreover, many of these databases use disparate storage formats but are linked to each other. So, an important issue concerning present biological resources is their availability and integration at single platform. This chapter provides an insight into existing biological resources with an aim to provide consolidated information at one place for ease of use and access by researchers, academicians and students.

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