scholarly journals Information retrieval algorithm of industrial cluster based on vector space

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 60-68
Author(s):  
Rongsheng Li ◽  
Nasruddin Hassan
Keyword(s):  
Information Retrieval ◽  
Energy Consumption ◽  
Vector Space ◽  
Industrial Cluster ◽  
Relevant Information ◽  
High Energy ◽  
Industrial Clusters ◽  
Retrieval Algorithm ◽  
Web Pages ◽  
Information Database

AbstractThe current information retrieval research on industrial clusters has low precision, low recall ratio, obvious delay and high energy consumption. Thus, in this paper, a information retrieval algorithm based on vector space for industrial clusters is proposed. By optimizing the unlawful labels in the database network, dividing the web pages of the industrial cluster information database and calculating the keyword scores of the relevant information of the industrial cluster corresponding to a web page, a set of well-divided database pages is obtained, and the purification of the industrial cluster information database is realized. According to the purification of industrial cluster information database, RFD algorithm is used to extract the page data features of purified industrial cluster information database. The extracted results are substituted into the information retrieval, and the vectors composed of retrieval units are used to describe the information of various types of industrial clusters and each retrieval. The matching results of information retrieval are obtained by calculating the correlation between the information of industrial clusters and the query, and the information retrieval of industrial clusters is completed. Experimental results show that the algorithm has high precision and recall ratio, short retrieval time and low energy consumption.

scholarly journals Large Scale Hotel Resource Retrieval Algorithm Based on Characteristic Threshold Extraction

2022 ◽  
Vol 16 ◽  
pp. 26-31
Author(s):  
Min Fang
Keyword(s):  
Energy Consumption ◽  
Data Processing ◽  
Large Scale ◽  
High Energy ◽  
Error Component ◽  
Retrieval Algorithm ◽  
Data Detection ◽  
Redundant Data ◽  
Variable Window ◽  
Resource Data

At present, the hotel resource retrieval algorithm has the problem of low retrieval efficiency, low accuracy, low security and high energy consumption, and this study proposes a large scale hotel resource retrieval algorithm based on characteristic threshold extraction. In the large-scale hotel resource data, the mass sequence is decomposed into periodic component, trend component, random error component and burst component. Different components are extracted, the singular point detection is realized by the extraction results, and the abnormal data in the hotel resource data are obtained. Based on the attribute of hotel resource data, the data similarity is processed with variable window, the total similarity of data is obtained, and the abnormal detection of redundant resource data is realized. The abnormal data detection results and redundant data detection results are substituted into the space-time filter, and the data processing is completed. The retrieval problem is identified, and the data processing results are replaced in the hotel resource retrieval based on the characteristic threshold extraction to achieve the normalization of data source and rule knowledge. The characteristic threshold and retrieval strategy are determined, and data fusion reasoning is carried out. After repeated iteration, effective solutions are obtained. The effective solution is fused to get the best retrieval result. Experimental results showed that the algorithm has higher retrieval accuracy, efficiency and security coefficient, and the average search energy consumption is 56n J/bit.

Search Engines and Meta Search Engines for Effective Information Retrieval and Scholarly Communication

2018 ◽  
pp. 1994-2008
Author(s):  
J. Vivekavardhan
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
World Wide ◽  
Scholarly Communication ◽  
Relevant Information ◽  
Web Pages ◽  
New Methodologies ◽  
Meta Search ◽  
Knowledge Manager ◽  
Information Scientist

Search Engines (SEs) and Meta-Search Engines (MSEs) are the tools that allows people to find information on the World Wide Web. SEs and MSEs on internet have improved continually with application of new methodologies to satisfy their users by providing them with relevant information. Understanding and Utilization of SEs and MSEs are useful for information scientist, knowledge manager, librarians and most importantly for authors and researchers for effective information retrieval and scholarly communication. The paper explores on how Search Engines and Meta-Search Engines discover web pages, indexes content, and provide search results. The paper discusses about the technological evolution of SEs and MSEs, working process and different types of SEs and MSEs. Finally paper presents conclusions and suggestions for further research.

Adaptive Ontology-Based Web Information Retrieval

2012 ◽  
pp. 152-170 ◽  
Author(s):  
Cédric Pruski ◽  
Nicolas Guelfi ◽  
Chantal Reynaud
Keyword(s):  
Information Retrieval ◽  
Data Structures ◽  
Web Search ◽  
Relevant Information ◽  
Web Pages ◽  
Web Information Retrieval ◽  
Domain Specific ◽  
Web Information ◽  
Expansion Technique ◽  
The Web

Finding relevant information on the Web is difficult for most users. Although Web search applications are improving, they must be more “intelligent” to adapt to the search domains targeted by queries, the evolution of these domains, and users’ characteristics. In this paper, the authors present the TARGET framework for Web Information Retrieval. The proposed approach relies on the use of ontologies of a particular nature, called adaptive ontologies, for representing both the search domain and a user’s profile. Unlike existing approaches on ontologies, the authors make adaptive ontologies adapt semi-automatically to the evolution of the modeled domain. The ontologies and their properties are exploited for domain specific Web search purposes. The authors propose graph-based data structures for enriching Web data in semantics, as well as define an automatic query expansion technique to adapt a query to users’ real needs. The enriched query is evaluated on the previously defined graph-based data structures representing a set of Web pages returned by a usual search engine in order to extract the most relevant information according to user needs. The overall TARGET framework is formalized using first-order logic and fully tool supported.

Adaptive Ontology-Based Web Information Retrieval

2011 ◽  
Vol 3 (3) ◽  
pp. 41-58 ◽  
Author(s):  
Cédric Pruski ◽  
Nicolas Guelfi ◽  
Chantal Reynaud
Keyword(s):  
Information Retrieval ◽  
Data Structures ◽  
Web Search ◽  
Relevant Information ◽  
Web Pages ◽  
Web Information Retrieval ◽  
Domain Specific ◽  
Web Information ◽  
Expansion Technique ◽  
Search Domain

Finding relevant information on the Web is difficult for most users. Although Web search applications are improving, they must be more “intelligent” to adapt to the search domains targeted by queries, the evolution of these domains, and users’ characteristics. In this paper, the authors present the TARGET framework for Web Information Retrieval. The proposed approach relies on the use of ontologies of a particular nature, called adaptive ontologies, for representing both the search domain and a user’s profile. Unlike existing approaches on ontologies, the authors make adaptive ontologies adapt semi-automatically to the evolution of the modeled domain. The ontologies and their properties are exploited for domain specific Web search purposes. The authors propose graph-based data structures for enriching Web data in semantics, as well as define an automatic query expansion technique to adapt a query to users’ real needs. The enriched query is evaluated on the previously defined graph-based data structures representing a set of Web pages returned by a usual search engine in order to extract the most relevant information according to user needs. The overall TARGET framework is formalized using first-order logic and fully tool supported.

Research of Information Retrieval Based on Web Page Segmentation

2012 ◽  
Vol 204-208 ◽  
pp. 4928-4931
Author(s):  
Yang Xin Yu
Keyword(s):  
Information Retrieval ◽  
Visual Similarity ◽  
Retrieval Algorithm ◽  
Web Pages ◽  
Web Page ◽  
Web Information Retrieval ◽  
Page Segmentation ◽  
Web Information ◽  
Future Search ◽  
Content Similarity

A Web information retrieval algorithm based on Web page segment is designed, the key idea of which is to segment each Web page into different topic areas or segments according to its HTML tags and contents since Web pages are semi-structure. First, the algorithm builds a HTML tag tree, and then it combines nodes in the tree under the rule of content similarity and visual similarity. During the process of retrieval and ranking, the algorithm makes full use of the segmentation information to sequence the relevant pages. The experimental results show that this method is able to improve the precision in search significantly and it is also a good reference for the design of the future search engines.

BIOCLIMATIC ANALYSIS OF MECHE'S HOUSE: A CONSTRUCTION ALTERNATIVE

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Mauro Cepeda Ortiz ◽  
Santiago Morales Flores ◽  
Enrique Villacis
Keyword(s):  
Energy Consumption ◽  
Architectural Design ◽  
Natural Ventilation ◽  
Relevant Information ◽  
High Energy ◽  
Climatic Conditions ◽  
Climate Conditions ◽  
Bioclimatic Design ◽  
Adaptive Comfort ◽  
Post Disaster

Meche's House is an alternative post-disaster construction, and this is the study of its bioclimatic approach showing that social and post-disaster buildings also need this kind of research. Tropical climate conditions lead to buildings having a high energy consumption for cooling loads. In Ecuador, the energy consumption of the residential area is 28.78% of final demand. Also, there is very little relevant information on the analysis of bioclimatic design in buildings, as well as specific analysis of interior comfort. The carried-out analysis process considered methods of bioclimatic evaluation, which mainly focuses on building the user's comfort. For this reason, in the first place, the site climatic conditions and possible passive intervention strategies were determined. Followed by the evaluation of natural ventilation with which it was possible to evaluate the effectiveness of natural ventilation through simulations in Computational Fluid Dynamics program. Furthermore, thermal comfort analysis using an Energy Plus program is used for comparing the internal temperature ranges versus indoor natural ventilation. Finally, the data is discussed under an adaptive comfort and user perception of satisfaction. This research confirms the need to carry out bioclimatic evaluations of projects conceived under a good line of architectural design, since only in this way will it be possible to demonstrate that the proposed considerations and strategies have positive or negative outcomes.

Search Engines and Meta Search Engines for Effective Information Retrieval and Scholarly Communication

2017 ◽  
pp. 312-329
Author(s):  
J. Vivekavardhan
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
World Wide ◽  
Scholarly Communication ◽  
Relevant Information ◽  
Web Pages ◽  
New Methodologies ◽  
Meta Search ◽  
Knowledge Manager ◽  
Information Scientist

Search Engines (SEs) and Meta-Search Engines (MSEs) are the tools that allows people to find information on the World Wide Web. SEs and MSEs on internet have improved continually with application of new methodologies to satisfy their users by providing them with relevant information. Understanding and Utilization of SEs and MSEs are useful for information scientist, knowledge manager, librarians and most importantly for authors and researchers for effective information retrieval and scholarly communication. The paper explores on how Search Engines and Meta-Search Engines discover web pages, indexes content, and provide search results. The paper discusses about the technological evolution of SEs and MSEs, working process and different types of SEs and MSEs. Finally paper presents conclusions and suggestions for further research.

Aplikasi Deteksi Kemiripan Tugas Paper

2017 ◽  
Vol 15 (2) ◽  
pp. 5
Author(s):  
Anthony Anggrawan ◽  
Azhari
Keyword(s):  
Information Retrieval ◽  
Vector Space ◽  
Vector Space Model ◽  
Mean Average Precision ◽  
Average Precision ◽  
Information Searching ◽  
Space Model ◽  
Model Method

Information searching based on users’ query, which is hopefully able to find the documents based on users’ need, is known as Information Retrieval. This research uses Vector Space Model method in determining the similarity percentage of each student’s assignment. This research uses PHP programming and MySQL database. The finding is represented by ranking the similarity of document with query, with mean average precision value of 0,874. It shows how accurate the application with the examination done by the experts, which is gained from the evaluation with 5 queries that is compared to 25 samples of documents. If the number of counted assignments has higher similarity, thus the process of similarity counting needs more time, it depends on the assignment’s number which is submitted.

Separation of Biologically Active Compounds by Membrane Operations

2017 ◽  
Vol 23 (2) ◽  
pp. 218-230 ◽  
Author(s):  
Xiaoying Zhu ◽  
Renbi Bai
Keyword(s):  
Energy Consumption ◽  
Bioactive Compounds ◽  
Membrane Fouling ◽  
Membrane Separation ◽  
Separation Efficiency ◽  
High Energy ◽  
Separation Processes ◽  
Membrane Processes ◽  
Separation Technology ◽  
Pressure Driven

Background: Bioactive compounds from various natural sources have been attracting more and more attention, owing to their broad diversity of functionalities and availabilities. However, many of the bioactive compounds often exist at an extremely low concentration in a mixture so that massive harvesting is needed to obtain sufficient amounts for their practical usage. Thus, effective fractionation or separation technologies are essential for the screening and production of the bioactive compound products. The applicatons of conventional processes such as extraction, distillation and lyophilisation, etc. may be tedious, have high energy consumption or cause denature or degradation of the bioactive compounds. Membrane separation processes operate at ambient temperature, without the need for heating and therefore with less energy consumption. The “cold” separation technology also prevents the possible degradation of the bioactive compounds. The separation process is mainly physical and both fractions (permeate and retentate) of the membrane processes may be recovered. Thus, using membrane separation technology is a promising approach to concentrate and separate bioactive compounds. Methods: A comprehensive survey of membrane operations used for the separation of bioactive compounds is conducted. The available and established membrane separation processes are introduced and reviewed. Results: The most frequently used membrane processes are the pressure driven ones, including microfiltration (MF), ultrafiltration (UF) and nanofiltration (NF). They are applied either individually as a single sieve or in combination as an integrated membrane array to meet the different requirements in the separation of bioactive compounds. Other new membrane processes with multiple functions have also been developed and employed for the separation or fractionation of bioactive compounds. The hybrid electrodialysis (ED)-UF membrane process, for example has been used to provide a solution for the separation of biomolecules with similar molecular weights but different surface electrical properties. In contrast, the affinity membrane technology is shown to have the advantages of increasing the separation efficiency at low operational pressures through selectively adsorbing bioactive compounds during the filtration process. Conclusion: Individual membranes or membrane arrays are effectively used to separate bioactive compounds or achieve multiple fractionation of them with different molecule weights or sizes. Pressure driven membrane processes are highly efficient and widely used. Membrane fouling, especially irreversible organic and biological fouling, is the inevitable problem. Multifunctional membranes and affinity membranes provide the possibility of effectively separating bioactive compounds that are similar in sizes but different in other physical and chemical properties. Surface modification methods are of great potential to increase membrane separation efficiency as well as reduce the problem of membrane fouling. Developing membranes and optimizing the operational parameters specifically for the applications of separation of various bioactive compounds should be taken as an important part of ongoing or future membrane research in this field.

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