Image/text automatic indexing and retrieval system using context vector approach

1995 ◽  
Author(s):  
Kent P. Qing ◽  
William R. Caid ◽  
Clara Z. Ren ◽  
Patrick McCabe
Keyword(s):  
Retrieval System ◽  
Automatic Indexing ◽  
Context Vector ◽  
Indexing And Retrieval ◽  
Vector Approach

scholarly journals Special Issue on Advances in Deep Learning

2020 ◽  
Vol 10 (9) ◽  
pp. 3172
Author(s):  
Diego Gragnaniello ◽  
Andrea Bottino ◽  
Sandro Cumani ◽  
Wonjoon Kim
Keyword(s):  
Deep Learning ◽  
Text Analysis ◽  
Autonomous Driving ◽  
Research Field ◽  
Media Content ◽  
Special Issue ◽  
Automatic Indexing ◽  
Automatic Translation ◽  
Indexing And Retrieval ◽  
Tremendous Impact

Nowadays, deep learning is the fastest growing research field in machine learning and has a tremendous impact on a plethora of daily life applications, ranging from security and surveillance to autonomous driving, automatic indexing and retrieval of media content, text analysis, speech recognition, automatic translation, and many others [...]

LocalContent: a personal scientific document retrieval system

2015 ◽  
Vol 33 (3) ◽  
pp. 373-385 ◽  
Author(s):  
Chih-Fong Tsai ◽  
Shih-Wen Ke ◽  
Kenneth McGarry ◽  
Ming-Yi Lin
Keyword(s):  
Language Processing ◽  
Retrieval System ◽  
Personal Information ◽  
Document Retrieval ◽  
Processing Technique ◽  
Content Type ◽  
Indexing And Retrieval ◽  
Database Indexing ◽  
Personal Archives ◽  
Indexing Term

Purpose – The purpose of this paper is to introduce a novel personal scientific document retrieval system. The most common approach taken for the storage of personal documents is to construct a hierarchical folder structure. Most users prefer searching for documents by manually traversing their organizational hierarchy until reaching the location where the target item is stored, then locating the specific documents within its directory or folder. However, this is very time-consuming, especially when the number of personal scientific documents is very large. Unfortunately, related personal information management (PIM) systems, which provide solutions for managing various types of personal information, have thus far made little progress at managing personal scientific documents. Design/methodology/approach – In this paper, we introduce the design of a personal scientific document retrieval system, namely, LocalContent. It is composed of database indexing and retrieval stages. During indexing, term feature extraction from scientific documents is performed by the natural language processing technique. The extracted terms are stored in the inverted index for later retrieval. For retrieval, a graphical user interface is provided by LocalContent, which allows users to search their personal scientific documents. Findings – The evaluation results based on 20 different personal archives taken from 20 graduate students show that LocalContent is simple to use and can facilitate the search for relevant scientific documents. Moreover, these users were willing to have a system which provides specialized search functions like LocalContent to explore their personal scientific documents in the future. Originality/value – LocalContent is a novel scientific document retrieval system and provides several particular functions of LocalContent including displaying the content summary of the query term frequency in each specific section of the retrieved documents, querying by local section specification and providing a number of recommended keywords related to the query terms.

Practical video indexing and retrieval system

1998 ◽  
Author(s):  
Yiqing Liang ◽  
Wayne H. Wolf ◽  
Bede Liu ◽  
Jeffrey R. Huang
Keyword(s):  
Retrieval System ◽  
Video Indexing ◽  
Indexing And Retrieval ◽  
Video Indexing And Retrieval

scholarly journals OVIS: ontology video surveillance indexing and retrieval system

2017 ◽  
Vol 6 (4) ◽  
pp. 295-316 ◽  
Author(s):  
Mohammed Yassine Kazi Tani ◽  
Abdelghani Ghomari ◽  
Adel Lablack ◽  
Ioan Marius Bilasco
Keyword(s):  
Video Surveillance ◽  
Retrieval System ◽  
Indexing And Retrieval

scholarly journals Automatic indexing and retrieval of encounter-specific evidence for point-of-care support

2010 ◽  
Vol 43 (4) ◽  
pp. 623-631 ◽  
Author(s):  
Dympna M. O’Sullivan ◽  
Szymon A. Wilk ◽  
Wojtek J. Michalowski ◽  
Ken J. Farion
Keyword(s):  
Point Of Care ◽  
Automatic Indexing ◽  
Indexing And Retrieval ◽  
Care Support
Sign in / Sign up

Export Citation Format

Share Document