基于模糊概念格的社会导航研究
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摘要
在Internet这样一个海量的信息世界中,用户可能迷失,也可能在一个未曾涉足的信息中不知所措。尽管当前的搜索引擎能够通过用户查询词来帮助人们获取一些信息,但要从庞大的搜索结果找到有用信息,有时显得非常困难。怎样帮助人们快速有效地找到自己感兴趣且价值更高的信息,是本文所要研究和解决的主要问题。
所幸的是,人类社会中存在的一种普遍现象——社会导航被引入到本领域,其主要目标是直接地或间接地利用他人的信息来帮助人们做出决策。将社会导航与搜索引擎相结合是引导人们在搜索引擎返回的大量结果中做出决策的有效方法。概念格是规则获取与知识表达的重要工具,但其所基于的形式背景大多是二值形式背景。而在实际中,大量的形式背景都是模糊的。因此,模糊概念格(FCL)是在模糊形式背景下进行数据分析与知识发现的一种有效的工具。
本文取得的主要研究成果如下:
1.提出了基于模糊概念格的社会导航模型。该模型主要通过获取用户需要导航的目标和社会经验来向用户提供导航。用户需要的导航目标是通过NavFCA插件与用户交互过程中获得的用户查询词,社会经验是通过从日志文件中抽取用户踪迹而构造出的模糊形式背景。通过将社会经验表示成模糊概念格这种有效的知识结构,社会导航的网页的URLs及其摘要由NavFCA插件显示给用户。同时,为实现本社会导航模型,设计并实现了如何获取用户踪迹、模糊形式背景生成、在模糊概念格上进行社会导航并显示给用户等一系列技术与算法。
2.提出并实现了模糊概念格构造算法(FCLB)。该算法从给定的模糊形式背景与模糊集集合中,生成模糊形式概念,自动建立并图形化显示模糊概念格。
3.设计并实现了基于模糊概念格的社会导航系统,并通过实验表明本系统能将用户踪迹处理成有用的知识结构,这种结构有助于智能搜索。
In the information world such as Internet, people will be lost or will be at a loss to act in an unknown environment. As we know, search engine can help people to find some information. However, to find useful information in the huge results of search engine is sometimes very difficult. So how to help people to find interesting and more effective information is the main issue of this paper.
Fortunately, social navigation the universal phenomenon in human society is introduced in this domain. The main aim of social navigation is to help people to take decisions using directly or indirectly information from other people. So, integrating social navigation with search engines is an efficient way to provide assistances supporting making progress after search engines return lots of results. Concept lattice is an important tool for rules acquiring and knowledge expressing. But the formal context of it based is usually a binary context. However, in fact, most of formal context are indefinite and fuzzy. So fuzzy concept lattice (FCL) is an effective tool for data analyzing and knowledge discovering.
The main contributions of this paper are listed below.
1. A new model of social navigation based on fuzzy concept lattice is put forward. As we know, the aim of navigation the user needed and the social experience are the two key factors for social navigation. In our social navigation model, the aim can be attained by the query words which is inputted by the users' themselves voluntarily in the process of the plug-in interface NavFCA devised by ourselves interacting with users; the social experience can be attained by the fuzzy formal context constructed by the related information extracted from log files. Through processing this social experience into fuzzy concept lattice the effective knowledge structure, the URLs and their abstracts of the navigated web pages can be showed to users by NavFCA. Besides this, algorithms and relative technologies of social navigation based on fuzzy concept lattice are proposed such as acquiring user trails, generating fuzzy formal concepts, social navigating on FCL etc.
2. A fast and automatic algorithm for FCL building is proposed, called FCLB algorithm, for generating fuzzy concepts from a given fuzzy formal context and a set of fuzzy sets, automatically building a fuzzy concept lattice and representing it graphically.
3. The social navigation system based on fuzzy concept lattice is designed and implemented. Experiments indicate that it can process surfing trails into useful knowledge structures which can be later used in intelligent searching.
所幸的是,人类社会中存在的一种普遍现象——社会导航被引入到本领域,其主要目标是直接地或间接地利用他人的信息来帮助人们做出决策。将社会导航与搜索引擎相结合是引导人们在搜索引擎返回的大量结果中做出决策的有效方法。概念格是规则获取与知识表达的重要工具,但其所基于的形式背景大多是二值形式背景。而在实际中,大量的形式背景都是模糊的。因此,模糊概念格(FCL)是在模糊形式背景下进行数据分析与知识发现的一种有效的工具。
本文取得的主要研究成果如下:
1.提出了基于模糊概念格的社会导航模型。该模型主要通过获取用户需要导航的目标和社会经验来向用户提供导航。用户需要的导航目标是通过NavFCA插件与用户交互过程中获得的用户查询词,社会经验是通过从日志文件中抽取用户踪迹而构造出的模糊形式背景。通过将社会经验表示成模糊概念格这种有效的知识结构,社会导航的网页的URLs及其摘要由NavFCA插件显示给用户。同时,为实现本社会导航模型,设计并实现了如何获取用户踪迹、模糊形式背景生成、在模糊概念格上进行社会导航并显示给用户等一系列技术与算法。
2.提出并实现了模糊概念格构造算法(FCLB)。该算法从给定的模糊形式背景与模糊集集合中,生成模糊形式概念,自动建立并图形化显示模糊概念格。
3.设计并实现了基于模糊概念格的社会导航系统,并通过实验表明本系统能将用户踪迹处理成有用的知识结构,这种结构有助于智能搜索。
In the information world such as Internet, people will be lost or will be at a loss to act in an unknown environment. As we know, search engine can help people to find some information. However, to find useful information in the huge results of search engine is sometimes very difficult. So how to help people to find interesting and more effective information is the main issue of this paper.
Fortunately, social navigation the universal phenomenon in human society is introduced in this domain. The main aim of social navigation is to help people to take decisions using directly or indirectly information from other people. So, integrating social navigation with search engines is an efficient way to provide assistances supporting making progress after search engines return lots of results. Concept lattice is an important tool for rules acquiring and knowledge expressing. But the formal context of it based is usually a binary context. However, in fact, most of formal context are indefinite and fuzzy. So fuzzy concept lattice (FCL) is an effective tool for data analyzing and knowledge discovering.
The main contributions of this paper are listed below.
1. A new model of social navigation based on fuzzy concept lattice is put forward. As we know, the aim of navigation the user needed and the social experience are the two key factors for social navigation. In our social navigation model, the aim can be attained by the query words which is inputted by the users' themselves voluntarily in the process of the plug-in interface NavFCA devised by ourselves interacting with users; the social experience can be attained by the fuzzy formal context constructed by the related information extracted from log files. Through processing this social experience into fuzzy concept lattice the effective knowledge structure, the URLs and their abstracts of the navigated web pages can be showed to users by NavFCA. Besides this, algorithms and relative technologies of social navigation based on fuzzy concept lattice are proposed such as acquiring user trails, generating fuzzy formal concepts, social navigating on FCL etc.
2. A fast and automatic algorithm for FCL building is proposed, called FCLB algorithm, for generating fuzzy concepts from a given fuzzy formal context and a set of fuzzy sets, automatically building a fuzzy concept lattice and representing it graphically.
3. The social navigation system based on fuzzy concept lattice is designed and implemented. Experiments indicate that it can process surfing trails into useful knowledge structures which can be later used in intelligent searching.
引文
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[6]. Svensson M., Hook K., Coste R., Designing and evaluating kalas: A social navigation system for food recipes, ACM Transactions on Computer-Human Interaction, (2005)1,374-400
[7]. Birukou A., Blanzieri E. and Giorgini P., Implicit Culture as a Tool for Social Navigation ,Workshop on the Social Navigation and Community-Based Adaptation Technologies at the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems,(2006)1, 20-23
[8]. Dieberger A., Dourish P., HAoAok K., et al, Social navigation: Techniques for building more usable systems, Interactions, (2000)7, 36-45
[9]. Rosenfeld L. , Morville P. , Information Architecture for the World Wide Web, Second Edition, O'Reilly, (2002)1,129-131
[10].Balabanovic M. , Shoham Y., Fab: content-based, collaborative recommendation, Communications of the ACM, (1997)40,66-72
[11]. Joseph A., Bradley N. M., Maltz D. et al, Grouplens: GroupLens: applying collaborative filtering to Usenet news, Communications of the ACM, (1997)40, 77-87
[12].Blanzieri E., Giorgini P., Massa P., et al, Implicit Culture for Multi-agent Interaction Support, Proceedings of the 9th International Conference on Cooperative Information Systems, Lecture Notes in Computer Science (LNCS), Springer-Verlag, (2001)2172,27-39
[13]. Svensson M ., Hook K. , Laaksolahti J., Social Navigation of Food Recipes, Proceedings of the SIGCHI conference on Human factors in computing systems, ACM Press, (2001)1,341-348
[14]. Wexelblat A., Footprints: History—Rich Tools for Information Foraging, In Proceeding of the CHI 99 Conference on Human Factors in Computing Systems, (1999)1,270-277
[15].Wexelblat A., History-based tools for navigation, In IEEE's 32nd Hawai'i international conference on system sciences (HICSS'99), Hawai: IEEE Computer Society Press, 1999
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[20].Brusilovsky P., Workshop on New Technologies for Personalized Information Access was held in Edinburgh, Scotland, UK, July 24th and 25th, 2005
[21].Meyer U., Wetzel S., Introducing History-Enriched Security Context Transfer to Enhance the Security of Subsequent Handover, Fourth IEEE International Conference on Pervasive Computing and Communications Workshops, (2006)1, 277-292
[22].Beydoun G., Kultchitsky R., Manasseh G., Evolving semantic web with social navigation,Expert Systems with Applications , (2007)32, 265-276
[23].Ganter B., Wille R., Formal concept analysis: Mathematical foundations, Springer -Verlag,1999
[24].Kent R. and Bowman C. M., Digital Libraries, conceptual Knowledge Systems and the Nebula interface, University of Arkansas, 1995
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[35].Georgescu G.,Popescu A.,Non-dual fuzzy connections,Archive Math,Logic,(2004)43,1009-1039
[36].Shi-Qing Fan,Wen-Xiu Zhang,Wei Xu,Fuzzy inference based on fuzzy concept lattice,Fuzzy Sets and Systems,(2006)157,3177-3187
[37].Zhongtian Liu,Yu Qiang and Wen Zhou,A fuzzy concept lattice model and its incremental construction algorithm,CHINESE JOURNAL OF COMPUTERS,(2007)30,184-188
[38].Zadeh L A,Outline of a new approach to the analysis of complex systems and decision processes,IEEE Trans.on Systems,Man,and Cybemetics,(1973)3,28-44
[39].Baldwin J.F.A new approach to approximate reasoning using a fuzzy logic,Fuzzy Sets and Systems,(1979)2,309-325
[40].Guan J.W.,Bell D.A.,A aproximate reasoning and evidence theory,In formations sciences,(1997)96,207-235
[41].Turksen L.B.,Zhao Z.,An approximate analogical reasoning approach based on similarity measures,IEEE Transactions on Systems Man and Cybernetics,(1989)18,1049-1056
[42].吴望名,区间值模糊集和区间值模糊推理,模糊系统与数学,(1992)6,38-48
[43].王国俊,模糊推理的一个新方法,模糊系统与数学,(1999)13,1-10
[44].秦克云,裴峥,模糊推理的α-3Ⅰ算法,模糊系统与数学,(2005)19,1-5
[45].宋士吉等,模糊推理的反向三Ⅰ算法,中国科学(E辑),(2002)32,43-53
[46].宋士吉等,模糊推理的反向三Ⅰ约束算法,自然科学进展,(2002)12,95-100
[47].Perfilieva I.,Tonis A,Compatibility of systems of fuzzy relation equations,Intemet J.Gen.Systems,(2000)29,511-528
[48].Zadeh L.A.,Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic,Fuzzy and Systems,(1997)90,111-127
[49].Herrera F.and Martinex L.,An approach for combining liniguistic and numerical infor mation based on 2-tuple fuzzy linguistic representation model in decision-making,Int,J.Uncertainty,Fuzziness,Knowledge-Based System,(2000)8,539-562
[50].Zheng P,Yang X,Lattice implication algebra model of linguistic variable truth and its inference,In applied Computation Interligence,(2006)1,93-98
[51].Yi liang-zhong,Xu Yang,Lukasiewicz Algebra Model of linguistic Values of Truth and Their Reasoning,Applied Artificial Intelligence,Proceeding of the 7th international FLINS Conference,(2006)1,87-94
[52].伊良忠,格蕴涵代数及语言真值不确定性推理研究,西南交通大学博士论文,2007
[53].强宇,刘宗田,吴强,时百盛,李云,模糊概念格在知识发现中的应用研究,计算机科学,(2005)32,16-20
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[2]. Dourish P., Chalmers M., Running out of space: models of information navigation (short paper), HCI'94 (British Computer Society), Accessible at ftp://parcftp.xerox.com/pub/euro parc/jpd/hci94-navigation.ps, 1994
[3]. Thomas E., The World Wide Web as Social Hypertext, Communications of the ACM,(1996)39,15-17
[4]. Dieberger A., Supporting social navigation on the world wide web, International Journal of Human-Computer Studies, (1997)46, 805-825
[5]. Svensson M., Defining and Designing Social Navigation, Bachelor's thesis Thesis,University of Stockholm, Stockholm, (2000)1,45-50
[6]. Svensson M., Hook K., Coste R., Designing and evaluating kalas: A social navigation system for food recipes, ACM Transactions on Computer-Human Interaction, (2005)1,374-400
[7]. Birukou A., Blanzieri E. and Giorgini P., Implicit Culture as a Tool for Social Navigation ,Workshop on the Social Navigation and Community-Based Adaptation Technologies at the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems,(2006)1, 20-23
[8]. Dieberger A., Dourish P., HAoAok K., et al, Social navigation: Techniques for building more usable systems, Interactions, (2000)7, 36-45
[9]. Rosenfeld L. , Morville P. , Information Architecture for the World Wide Web, Second Edition, O'Reilly, (2002)1,129-131
[10].Balabanovic M. , Shoham Y., Fab: content-based, collaborative recommendation, Communications of the ACM, (1997)40,66-72
[11]. Joseph A., Bradley N. M., Maltz D. et al, Grouplens: GroupLens: applying collaborative filtering to Usenet news, Communications of the ACM, (1997)40, 77-87
[12].Blanzieri E., Giorgini P., Massa P., et al, Implicit Culture for Multi-agent Interaction Support, Proceedings of the 9th International Conference on Cooperative Information Systems, Lecture Notes in Computer Science (LNCS), Springer-Verlag, (2001)2172,27-39
[13]. Svensson M ., Hook K. , Laaksolahti J., Social Navigation of Food Recipes, Proceedings of the SIGCHI conference on Human factors in computing systems, ACM Press, (2001)1,341-348
[14]. Wexelblat A., Footprints: History—Rich Tools for Information Foraging, In Proceeding of the CHI 99 Conference on Human Factors in Computing Systems, (1999)1,270-277
[15].Wexelblat A., History-based tools for navigation, In IEEE's 32nd Hawai'i international conference on system sciences (HICSS'99), Hawai: IEEE Computer Society Press, 1999
[16].Blunt R., Ahearn C. , Creating a virtual learning community, In The sixth international conference on asynchronous learning networks, Maryland, 2000
[17].Friedman B., Peter H., Human values, ethics, and design, The human-computer interaction handbook: fundamentals, evolving technologies and emerging applications, Lawrence Erlbaum Associates, Inc., Mahwah, NJ, 2002
[18].Svensson M., Hook K. , Evaluating social trails, Conference on Human Factors in Computing Systems, CHI '03 extended abstracts on Human factors in computing systems (2003)1, 844-855
[19].Hook K., Benyon D., Munro A J., Designing information spaces: the social navigation approach, Springer-Verlag, London, 2003
[20].Brusilovsky P., Workshop on New Technologies for Personalized Information Access was held in Edinburgh, Scotland, UK, July 24th and 25th, 2005
[21].Meyer U., Wetzel S., Introducing History-Enriched Security Context Transfer to Enhance the Security of Subsequent Handover, Fourth IEEE International Conference on Pervasive Computing and Communications Workshops, (2006)1, 277-292
[22].Beydoun G., Kultchitsky R., Manasseh G., Evolving semantic web with social navigation,Expert Systems with Applications , (2007)32, 265-276
[23].Ganter B., Wille R., Formal concept analysis: Mathematical foundations, Springer -Verlag,1999
[24].Kent R. and Bowman C. M., Digital Libraries, conceptual Knowledge Systems and the Nebula interface, University of Arkansas, 1995
[25].Corbett D., Burrow A., Kowledge Reuse in SEED Exploiting Conceptual Graphs,International Conference on Conceptual Graphs(ICC'96), (1996)1, 56-60
[26].Nijwoua P., and Mephu N. E., Back from experimentation:A study of leamig bias in Legal-E, In proceeding of Benelux Conference on Machin Learning, Maastrich, (1996)1,57-68
[27].Goguen J. A., L-fuzzy sets, Journal of Mathematical Analysis and Applications, (1967)18,145-174
[28].Burusco A. and Fuentes R., The study of the L-fuzzy concept lattice, Mathware Soft Comput,(1994)1,209-218
[29].Burusco A., Fuentes R., Construction of the L-fuzzy concept lattice, Fuzzy Sets and Systems, (1998)97,109-114
[30].Belohlavek R., Similarity relations in concept lattice, Logic Computation, (2000)10 823-845
[31].Belohlavek R., Fuzzy Galois connections, Math, Logic Quarterly, (1999)45,497-504
[32].Belohlavek R.,Lattices of fixed points of fuzzy Galois connections,Math,Logic Quarterly,(2001)47,111-116
[33].Belohlavek R.,Fuzzy Relational Systems:Foundations and Principles,Kluwer Academic Publishers,NewYork,2002
[34].Belohlavek R.,Concept lattices and order in fuzzy logic,Ann,Pure Appl,Logic,(2004)128,277-298
[35].Georgescu G.,Popescu A.,Non-dual fuzzy connections,Archive Math,Logic,(2004)43,1009-1039
[36].Shi-Qing Fan,Wen-Xiu Zhang,Wei Xu,Fuzzy inference based on fuzzy concept lattice,Fuzzy Sets and Systems,(2006)157,3177-3187
[37].Zhongtian Liu,Yu Qiang and Wen Zhou,A fuzzy concept lattice model and its incremental construction algorithm,CHINESE JOURNAL OF COMPUTERS,(2007)30,184-188
[38].Zadeh L A,Outline of a new approach to the analysis of complex systems and decision processes,IEEE Trans.on Systems,Man,and Cybemetics,(1973)3,28-44
[39].Baldwin J.F.A new approach to approximate reasoning using a fuzzy logic,Fuzzy Sets and Systems,(1979)2,309-325
[40].Guan J.W.,Bell D.A.,A aproximate reasoning and evidence theory,In formations sciences,(1997)96,207-235
[41].Turksen L.B.,Zhao Z.,An approximate analogical reasoning approach based on similarity measures,IEEE Transactions on Systems Man and Cybernetics,(1989)18,1049-1056
[42].吴望名,区间值模糊集和区间值模糊推理,模糊系统与数学,(1992)6,38-48
[43].王国俊,模糊推理的一个新方法,模糊系统与数学,(1999)13,1-10
[44].秦克云,裴峥,模糊推理的α-3Ⅰ算法,模糊系统与数学,(2005)19,1-5
[45].宋士吉等,模糊推理的反向三Ⅰ算法,中国科学(E辑),(2002)32,43-53
[46].宋士吉等,模糊推理的反向三Ⅰ约束算法,自然科学进展,(2002)12,95-100
[47].Perfilieva I.,Tonis A,Compatibility of systems of fuzzy relation equations,Intemet J.Gen.Systems,(2000)29,511-528
[48].Zadeh L.A.,Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic,Fuzzy and Systems,(1997)90,111-127
[49].Herrera F.and Martinex L.,An approach for combining liniguistic and numerical infor mation based on 2-tuple fuzzy linguistic representation model in decision-making,Int,J.Uncertainty,Fuzziness,Knowledge-Based System,(2000)8,539-562
[50].Zheng P,Yang X,Lattice implication algebra model of linguistic variable truth and its inference,In applied Computation Interligence,(2006)1,93-98
[51].Yi liang-zhong,Xu Yang,Lukasiewicz Algebra Model of linguistic Values of Truth and Their Reasoning,Applied Artificial Intelligence,Proceeding of the 7th international FLINS Conference,(2006)1,87-94
[52].伊良忠,格蕴涵代数及语言真值不确定性推理研究,西南交通大学博士论文,2007
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