scholarly journals An information retrieval system for computerized patient records in the context of a daily hospital practice: the example of the Léon Bérard Cancer Center (France)

2014 ◽  
Vol 05 (01) ◽  
pp. 191-205 ◽  
Author(s):  
P. Biron ◽  
C. Pezet ◽  
C. Sebban ◽  
E. Barthuet ◽  
T. Durand ◽  
...  
Keyword(s):  
Information System ◽  
Full Text ◽  
Medical Records ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Cancer Center ◽  
Patient Records ◽  
Text Search ◽  
Full Text Search ◽  
It Department

SummaryBackground: A full-text search tool was introduced into the daily practice of Léon Bérard Center (France), a health care facility devoted to treatment of cancer. This tool was integrated into the hospital information system by the IT department having been granted full autonomy to improve the system.Objectives: To describe the development and various uses of a tool for full-text search of computerized patient records.Methods: The technology is based on Solr, an open-source search engine. It is a web-based application that processes HTTP requests and returns HTTP responses. A data processing pipeline that retrieves data from different repositories, normalizes, cleans and publishes it to Solr, was integrated in the information system of the Leon Bérard center. The IT department developed also user interfaces to allow users to access the search engine within the computerized medical record of the patient.Results: From January to May 2013, 500 queries were launched per month by an average of 140 different users. Several usages of the tool were described, as follows: medical management of patients, medical research, and improving the traceability of medical care in medical records. The sensitivity of the tool for detecting the medical records of patients diagnosed with both breast cancer and diabetes was 83.0%, and its positive predictive value was 48.7% (gold standard: manual screening by a clinical research assistant).Conclusion: The project demonstrates that the introduction of full-text-search tools allowed practitioners to use unstructured medical information for various purposes.Citation: Biron P; Metzger MH; Pezet C; Sebban C; Barthuet E; Durand T. An information retrieval system for computerized patient records in the context of a daily hospital practice: the example of the Léon Bérard Cancer Center (France)Appl Clin Inf 2014; 5: 191–205http://dx.doi.org/10.4338/ACI-2013-08-CR-0065

Design and Implementation of Full-Text Retrieval System for People’s Daily Annotated Corpus

2011 ◽  
Vol 135-136 ◽  
pp. 369-374
Author(s):  
Yang Sen Zhang ◽  
Gai Juan Huang
Keyword(s):  
Full Text ◽  
Retrieval System ◽  
Search Algorithm ◽  
Text Retrieval ◽  
Index Structure ◽  
Text Search ◽  
Full Text Search ◽  
People’S Daily ◽  
Full Text Retrieval ◽  
People's Daily

In this paper, we have designed and realized a efficient full-text retrieval system for the basic annotation People's Daily Corpus based on the inverted index technology. According to the characteristics of the basic annotation People’s Daily Corpus data, we have analyzed the methods and strategies of system implementing thoroughly. On the basis of comparing the various schemes, we have put forward to the three levels index structure of Chinese character, word and address set, and given the design approach of each level index dictionary structure. After converting the unstructured People’s Daily corpus into index structured data, we realized the full-text search algorithm correspond to the proposed index structure. Experimental results show that the proposed search algorithm has achieved the target of "ten millions Chinese characters, response in a second", improved the speed of the People's Daily Corpus full-text search.

Beyond use statistics: Recall, precision, and relevance in the assessment and management of academic libraries

2016 ◽  
Vol 48 (4) ◽  
pp. 340-352 ◽  
Author(s):  
William H. Walters
Keyword(s):  
Information System ◽  
Information Retrieval ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Academic Community ◽  
Learning Goals ◽  
Performance Goals ◽  
Collection Development ◽  
Academic Mission ◽  
The University

Although use statistics are often used in the assessment of library collections and services, they are of limited value in evaluating the library’s effectiveness as an information system. This essay highlights three concepts from the information retrieval literature—recall, precision, and relevance—and describes a standard of relevance that accounts for the learning goals of the academic community as well as the performance goals of students. It also demonstrates how the academic mission of the university can be incorporated into the assessment and management of the library as an information retrieval system. The discussion concludes with guidelines for the assessment of recall and precision as well as suggestions for the integration of these concepts into library collection development, cataloging/access, reference, and instruction.

GPU Computation for Online Realtime Multi-Pattern Matching

2013 ◽  
Vol 284-287 ◽  
pp. 3428-3432 ◽  
Author(s):  
Yu Hsiu Huang ◽  
Richard Chun Hung Lin ◽  
Ying Chih Lin ◽  
Cheng Yi Lin
Keyword(s):  
Parallel Computation ◽  
Pattern Matching ◽  
Full Text ◽  
Network Performance ◽  
Text Search ◽  
Full Text Search ◽  
Network Intrusion ◽  
Speed Up ◽  
Set Up ◽  
Gpu Implementation

Most applications of traditional full-text search, e.g., webpage search, are offline which exploit text search engine to preview the texts and set up related index. However, applications of online realtime full-text search, e.g., network Intrusion detection and prevention systems (IDPS) are too hard to implementation by using commodity hardware. They are expensive and inflexible for more and more occurrences of new virus patterns and the text cannot be previewed and the search must be complete realtime online. Additionally, IDPS needs multi-pattern matching, and then malicious packets can be removed immediately from normal ones without degrading the network performance. Considering the problem of realtime multi-pattern matching, we implement two sequential algorithms, Wu-Manber and Aho-Corasick, respectively over GPU parallel computation platform. Both pattern matching algorithms are quite suitable for the cases with a large amount of patterns. In addition, they are also easier extendable over GPU parallel computation platform to satisfy realtime requirement. Our experimental results show that the throughput of GPU implementation is about five to seven times faster than CPU. Therefore, pattern matching over GPU offers an attractive solution of IDPS to speed up malicious packets detection among the normal traffic by considering the lower cost, easy expansion and better performance.

scholarly journals Application of Full Text Search Engine Based on Lucene

2012 ◽  
Vol 02 (04) ◽  
pp. 106-109 ◽  
Author(s):  
Rujia Gao ◽  
Danying Li ◽  
Wanlong Li ◽  
Yaze Dong
Keyword(s):  
Search Engine ◽  
Full Text ◽  
Text Search ◽  
Full Text Search

Recommender Systems in Digital Libraries Using Artificial Intelligence and Machine Learning

2021 ◽  
pp. 162-178
Author(s):  
Namik Delilovic
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Digital Libraries ◽  
Full Text ◽  
Text Search ◽  
Full Text Search ◽  
Artificial Intelligence Techniques ◽  
Search Results ◽  
Advanced Search ◽  
Search Field

Searching for contents in present digital libraries is still very primitive; most websites provide a search field where users can enter information such as book title, author name, or terms they expect to be found in the book. Some platforms provide advanced search options, which allow the users to narrow the search results by specific parameters such as year, author name, publisher, and similar. Currently, when users find a book which might be of interest to them, this search process ends; only a full-text search or references at the end of the book may provide some additional pointers. In this chapter, the author is going to give an example of how a user could permanently get recommendations for additional contents even while reading the article, using present machine learning and artificial intelligence techniques.

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