Latent Dirichlet allocation Feature-based retrieval models view documents as vectors of values of feature functions or just features and seek the best way to combine these features into a single relevance score, typically by learning to rank methods. Feature functions are arbitrary functions of document and query, and as such can easily incorporate almost any other retrieval model as just another feature. This fact is usually represented in vector space models by the orthogonality assumption of term vectors or in probabilistic models by an independency assumption for term variables. Models with immanent term interdependencies allow a representation of interdependencies between terms.
Inetrnet of Things IoT is a broadly recognized era over the planet and this is ascribable to the growing enthusiasm of a new concept known as Big Data. This last is a new term which describes the process of collecting and analysing information of different form that is available publicly in enormous volumes.
Searches on Google, social networks, and sales web sites are sources which feed the ocean. In the light of this remarkable development, the data analysts and computer scientists had focused their interest on this treasure in order to benefit from it in enhancing daily life of individual users and commercial community.
Consequently, new powerful and clever algorithms have been developed to analyse these data in order to extract valuable decisions.
From that, Big Data can be simply defined as the ability of diving within ocean of data of different forms to extract hidden patterns and IOT represents the exchange of information from real-world devices with the Internet where sensing a complex environment, connectivity, scalability, and privacy are the major problems that IoT suffers from since its creation.
Objective This special issue aims to collect and offer the scientific community new advancement of exploration, creation and development of solutions in internet of thigs IoT and big data challanges. We intended to discuss and share original research works and practical experiences by providing the latest and most innovative contributions in such complex and huge environments like Big Data and IoT domains.
Data center and Big data analytic. Private information retrieval in cloud computing. Metaheuristic algorithm in IOT challenges. Internet of things and Organizational Vulnerability Analysis. Trust Models and Trust Management. Security and Privacy for Ubiquitous intelligence systems.
Security and Privacy in E-Health. Grid, Internet and Middleware Computing. Bio-inspiration in Pervasive Networks and Communication. Metaheuristic algorithms in Semantic Analysis. Network Measurement for Smart Cities.
Machine learning in IOT. Submission Procedure Researchers and practitioners are invited to submit papers for this special theme issue on Advanced Research in Internet of Things IoT: Applications, Services, and Implementations on or before September 20, All submissions must be original and may not be under review by another publication.
All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.
All submissions and inquiries should be directed to the attention of:Cross-Language Information Retrieval (The Information Retrieval Series) [Gregory Grefenstette] on attheheels.com *FREE* shipping on qualifying offers.
Most of the papers in this volume were first presented at the Workshop on Cross-Linguistic Information Retrieval that was held August Search Engines: Information Retrieval in Practice is ideal for introductory information retrieval courses at the undergraduate and graduate level in computer science, information science and computer engineering departments.
It is also a valuable tool for search engine and information retrieval professionals. Written by a leader in the field of information retrieval, Search Engines.
The Economics Daily Real average hourly earnings up percent over the year ending October November 21, Real average hourly earnings for all employees increased percent from October to October School of Computing, College of Computing and Digital Media South Wabash Avenue Chicago, IL Phone: () FAX: () The mission of the International Journal of Information Retrieval Research (IJIRR) is to provide an outlet for researchers to present their research and obtain inspiration in the areas of information retrieval, computer science, and information science.
Focusing on theories, methods, technologies, and tools, IJIRR is aimed towards information. Through those projects, we study various cutting-edge data management research issues including information extraction and integration, large scale data analysis, effective data exploration, etc., using a variety of techniques, such as information retrieval, data mining and machine learning.