面向问题智能处理的基元−因素空间模型研究

李兴森; 许立波; 刘海涛

doi:10.12052/gdutxb.180135

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面向问题智能处理的基元−因素空间模型研究

可拓论坛 | 更新时间：2026-05-27

- 面向问题智能处理的基元−因素空间模型研究
- A Research on Problem Oriented Intelligent Processing Model by Basic-Element and Factor Space
- 广东工业大学学报 2019年36卷第1期页码：1-9
- 作者机构：
  
  1. 广东工业大学可拓学与创新方法研究所,广东,广州,510006
  2. 浙江大学宁波理工学院计算机与数据工程学院中澳智能计算与数据管理研究中心,浙江,宁波,315100
  3. 辽宁工程技术大学理学院,辽宁,阜新,125105
- 作者简介：
  
  李兴森(1968−)，男，教授，博士，主要研究方向为可拓学与智能创新
- 基金信息：
  
  国家自然科学基金资助项目(71271191);浙江省自然科学基金资助项目(LY18F020001，LY16G010010);教育部人文社会科学研究项目(18YJAZH049)
- DOI：10.12052/gdutxb.180135
  中图分类号： TP315;F49
- 网络首发：2019-01-25，
  
  纸质出版：2019
- 稿件说明：
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李兴森, 许立波, 刘海涛. 面向问题智能处理的基元−因素空间模型研究[J]. 广东工业大学学报, 2019, 36(1): 1-9.

Li Xing-sen, Xu Li-bo, Liu Hai-tao. A Research on Problem Oriented Intelligent Processing Model by Basic-Element and Factor Space[J]. 2019, 36(1): 1-9.
李兴森, 许立波, 刘海涛. 面向问题智能处理的基元−因素空间模型研究[J]. 广东工业大学学报, 2019, 36(1): 1-9. DOI： 10.12052/gdutxb.180135.

Li Xing-sen, Xu Li-bo, Liu Hai-tao. A Research on Problem Oriented Intelligent Processing Model by Basic-Element and Factor Space[J]. 2019, 36(1): 1-9. DOI： 10.12052/gdutxb.180135.

摘要

互联网已成为获取信息的重要来源

但仅依靠信息搜索引擎等现有技术仍难以从海量信息中智能化挖掘知识为解决问题服务

面向问题处理的互联网知识搜索的模型与算法等问题一直未得到有效解决. 知识搜索引擎要实现智能化解决问题的服务

关键是必须研究面向问题处理的互联网信息的智能重构模型. 基元−因素空间模型以可拓学基元理论、因素空间理论和智能知识管理理论为基础

交叉研究从互联网海量信息资源中抽取对象、属性和量值

重组互联网信息

自动构建领域基元的方法及从领域信息中挖掘特定问题的因素空间以获取领域知识的智能算法. 在动态基元信息、专家经验知识与因素空间融合的模式与算法基础上

开发模拟仿真软件以验证动态知识基元及因素库协同进行互联网信息重组的理论与方法

为利用互联网生成解决问题的创新策略和研发新一代面向问题处理的知识搜索引擎提供理论基础和新的方法支撑.

Abstract

The Internet has become an important way of obtaining information

but it is still difficult to provide aids to problem solving. Problem solving oriented knowledge searching in the Internet has not been solved thoroughly. The key factor is the reconstruction of web information. The combination of network and intelligence will bring the knowledge-based application of web information into a new stage. A cross-study is proposed on the novel hybrid method of extracting the objects

attributes

and values from the mass information of internet with simulation and automatically building the field basic elements on macro information based on Extenics

factor space theory and intelligent knowledge. In addition

a lot of future research directions are put forward

such as on intelligent algorithm which collects correlative factors of special problem from the field of information for acquiring domain knowledge. The research may provide theoretical basis and new methods for using the internet to generate the innovative strategy of problem solving and examine a new generation of problem-solving oriented knowledge search engine.

关键词

Keywords

references

RAHMAN M. Search engines going beyond keyword search: a survey [J]. International Journal of Computer Applications, 2013, 75(17): 1-8.

ZHANG Q H, XING Y K, ZHOU Y L. The incremental knowledge acquisition algorithm based on granular computing [J]. Journal of Electronics Information Technology, 2011, 33(2): 435-441.

WANG P Z, SUGENO M. The background structure of factor field and fuzzy sets [J]. Fuzzy Mathematics, 1982(2): 45-54.

WANG P Z. Factor spaces and factor data-bases [J]. Journal of Liaoning Technical University (Natural Science), 2013, 32(10): 1-8.

WANG P Z. Factor space and data science [J]. Journal of Liaoning Technical University (Natural Science), 2015, 34(2): 273-280.

WANG P Z, LIU Z L, SHI Y, et al . Factor space, the theoretical base of data science [J ] . Annals of Data Science, 2014, 1(2): 233-2 51.

汪培庄, 李洪兴. 知识表示的数学理论[M]. 天津: 天津科技出版社, 1994.

刘增良, 刘有才. 因素神经网络理论及实现策略研究[M]. 北京: 北京师范大学出版社, 1992.

ZENG W Y, LI D Q, WANG P Z. Variable weight decision making and balance function analysis based on factor space [J]. International Journal of Information Technology Decision Making, 2016, 15(5): 999-1014.

ZHOU L, SUN K, LI H. Multifactorial decision making based on type-2 fuzzy sets and factor space approach [J]. Journal of Intelligent Fuzzy Systems, 2016, 30(4): 2257-2266.

WANG H D, GUO S Z. DFE decision-making based on outer-enveloping of feedback extension in factor spaces [J]. Computer Engineering and Applications, 2015, 51(15): 148-152.

CUI T J, MA Y D. Definition of attribute circle in factor space and its application in object classification [J]. Computer Engineering Science, 2015, 31(11): 2169-2174.

CAI W. Extension set and non-compatible problem [J]. Science Exploration, 1983(1): 83-97.

CAI W, SHI Y. Extenics: its significance in science and prospects in application [J]. Journal of Harbin Institute of Technology, 2006, 38(7): 1079-1086.

TU X Y. Develop new research methods in new fields [J]. Science Technology Review, 2014, 32(36): 117.

ZHONG Y X. Comments on “Extenics” [J]. Chinese Science Bulletin, 2013(13): 1188-1189.

杨春燕, 蔡文. 可拓学[M]. 北京: 科学出版社, 2013.

李幼平. 可拓学: 沟通自然科学与社会科学的桥梁[J]. 科技导报, 2014, 32(36): 1, 3.

CHEN W W, YANG C Y, HUANG J C. Extension knowledge and extension knowledge reasoning [J]. Journal of Harbin Institute of Technology, 2006, 38(7): 1094-1096.

杨春燕, 汤龙. 中国人工智能学会系列研究报告—中国原创学科可拓学发展报告2016[R]. 北京: 北京邮电大学出版社, 2017.

SMARANDACHE F. Generalizations of the distance and dependent function in Extenics to 2D, 3D, and n-D [J]. Global Journal of Science Frontier Research, 2012, 12(8): 47-60.

SANDRU O I, LUIGE V, PAUL S. Multidimensional Extenics theory [J]. University Politehnica of Bucharest Scientific Bulletin-Series A: Applied Mathematics and Physics, 2013, 75(1): 3-12.

VLADAREANU V, SMARANDACHE F, VLADAREANU L. Extension hybrid force-position robot control in higher dimensions [J]. Applied Mechanics and Materials, 2013(332): 260-269.

蔡文, 杨春燕, 陈文伟, 等. 可拓集与可拓数据挖掘[M]. 北京: 科学出版社, 2008.

LI X S, ZHANG H, ZHU Z, et al . An intelligent transformation knowledge mining method based on Extenics [J ] . Journal of Internet Technology, 2013, 14(2): 315-325.

CUI C S, LAI K, CHEN J. Research on content-based recommendation of ecbased on basic element theory [J]. Journal of Systems Science and Mathematical Sciences, 2015, 35(10): 1209-1218.

李兴森, 石勇, 张玲玲. 从信息爆炸到智能知识管理[M]. 北京: 科学出版社, 2010.

LI X S, LI L, CHEN Z. Toward Extenics-based innovation model on intelligent knowledge management [J]. Annals of Data Science, 2014, 1(1): 127-148.

LI X S, TIAN Y, SMARANDACHE F, ALEX R. An extension collaborative innovation model in the context of big data [J]. International Journal of Information Technology Decision Making, 2015, 14(1): 69-91.

YANG C Y, CAI W. Generating creative ideas for production based on Extenics [J]. Journal of Guangdong University of Technology, 2016, 33(1): 12-16.

YU Z W, LI X S. Modeling of basic-element and its application [J]. Journal of Guangdong University of Technology, 2015, 32(3): 5-9.

XU H, CHEN H W, ZONG X L. Semantic-mismatching of management information for software-defined networking based on extension theory [J]. Journal of Guangdong University of Technology, 2017, 34(4): 17-21.

LI W J, YANG C Y. A Formal research on user needs and functions of products based on affair-element theory [J]. Journal of Guangdong University of Technology, 2017, 34(6): 1-8.

TAO X, LI W H, WANG Z F. Construction of howNet-based extendable domain information element base [J]. CAAI Transactions on Intelligent Systems, 2015, 10(5): 790-796.

WANG J L, LI X S. On basic element expression and construction of the unified content label [J]. Journal of Guangdong University of Technology, 2014, 31(2): 14-20.

LI Q X, LI X S. The method to construct elementary dependent function on single interval [J]. Key Engineering Materials, 2011, 476: 651-654.

GUDIVADA V N, RAO D, PARIS J. Understanding search engine optimization [J]. Computer, 2015, 48(10): 145-154.

HONG J, HE Z, BELL D A. An evidential approach to query interface matching on the deep web [J]. Information Systems, 2010, 35(2): 140.

KIM K, TSE E. Inferior search engine's optimal choice: knowledge-sharing service versus search quality [J]. Electronic Commerce Research and Applications, 2014, 13(6): 387-401.

BALSOY O, JIN Y, AYDIN G. Automating metadata web service deployment for problem solving environments [J]. Future Generation Computer Systems, 2005, 21(6): 910-919.

CHEN L, SHADBOLT N R, GOBLE C. Managing semantic metadata for web/grid services [J]. International Journal of Web Services Research, 2006, 3(4): 73-94.

GUO W N, SI L. Investigation and analysis on semantic search engines abroad [J]. Library and Information Service, 2013, 57(23): 121-129.

LAI L F, WU C C, LIN P Y, et al . Developing a fuzzy search engine based on fuzzy ontology and semantic search [J ] . IEEE International Conference on Fuzzy Systems, 2011: 2684-2689.

SHAH D, SOMAIYA J, NAIR S, et al . Fuzzy semantic search engine [J ] . International Journal of Computer Applications, 2014, 107(15): 25-27.

TAHA K, ELMASRI R. BusSEngine: a business search engine [J]. Knowledge and Information Systems, 2010, 23(2): 153-197.

LI J H, SHI P, HU C J. Overview of ontology search and ranking [J]. Journal of Chinese Computer Systems, 2013, 34(10): 2396-2406.

MYLONAS P, VALLET D, CASTELLS P, et al . Personalized information retrieval based on context and ontological knowledge [J ] . The Knowledge Engineering Review, 2008, 23(1): 73-100.

MIZZARO S, VASSENA L. A social approach to context-aware retrieval [J]. World Wide Web, 2011, 14(4): 377-405.

LIU J, XU H B, JIA Y T, et al . Dynamic knowledge network modeling orient to intelligent search [J ] . Telecommunications Science, 2014, 30(10): 64-70.

PETERS S, RUECKEMANN C P, SANDER-BEUERMANN W. A new approach towards vertical search engines-intelligent focused crawling and multilingual semantic techniques[J]. Webist 2010: Proceedings of the 6th International Conference on Web Information Systems and Technologies, 2012: 181-186.

TAHA K, ELMASRI R. XCDSearch: an XML context-driven search engine [J]. IEEE Transactions on Knowledge and Data Engineering, 2010, 22(12): 1781-1796.

RODRIGUEZ-GARCIA M A, RAFAEL V, FRANCISCO G. Ontology-based annotation and retrieval of services in the cloud [J]. Knowledge-Based Systems, 2014, 56: 15-25.

KOO D M, CHOI Y Y. Knowledge search and people with high epistemic curiosity [J]. Computers in Human Behavior, 2010, 26(1): 12-22.

SHROFF, GAUTAM. The intelligent web: search, smart algorithms, and big data[J]. Oxford University Press, 2013.

陈震, 曹军威. 信息中心网络[M]. 北京: 清华大学出版社, 2013.

HONG, JUNE S. Development of constraint-based problem solving framework for the semantic web [J]. Entrue Journal of Information Technology, 2011, 10(2): 239-250.

ANNELIES R, SCHELLENS T, DE W B. Promoting metacognitive regulation through collaborative problem solving on the web: when scripting does not work [J]. Computers in Human Behavior, 2016, 58: 325-342.

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