Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence Concept 집단지성 ( 集体智慧 /collective intelligence) 란 다수의 개체들이 서로 협력 혹은 경쟁을 통하여 얻게 되는 지적 능력에 의한 결 과로 얻어진 집단적 능력을 말한다. 집단적 지적 능력을 통해 개체적으로는 미미하게 보이는 동물, 사람의 능력을 모으는 과정을 통한 결정 능력의 다양한 형태 로 한 개체의 능력 범위를 넘어선 힘을 발휘할 수도 있다고, 이 분야는 사회학, 경영학, 컴퓨터 공학 등에서 연구되고 있다 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Collective Intelligence History 1910 년대 하버드 대학 교수이자 곤충학자인 William Morton Wheeler 가 개미의 사회적 행동을 관찰하면서 처음 제시했다. 휠러는 개체로는 미미한 개미가 공동체로서 협업 ( 協業 ) 하여 거대한 개미집을 만들 어내는 것을 관찰하였고, 이를 근거로 개미는 개체로서는 미미하지만 군집 ( 群集 ) 하 여서는 높은 지능체계를 형성한다고 설명하였다. Pierre Levy 는 사이버 공간의 집단지성을 제시하였다. 그는 " 누구나 자신의 공간 ( 사이트 ) 를 가지고 일종의 형성하는 시대가 오면 어디 에나 분포하고, 지속적으로 가치 부여되며, 실시간으로 조정되고, 역량의 실제적 동원에 이르는 집단지성이 발현될 것 " 이라고 주장하였다 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Collective Intelligence Four principles CI 는 대규모 협조이다. 이런 계념을 실현하기 위해서는 4 가 지 기본 원칙이 필요하다. Openness Peering ( 对等 ) Sharing Acting globally Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Collective Intelligence Types Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Collective Intelligence Examples Wikipedia Wikipedia 의 발전 과정은 지식 · 정보의 생산자나 수혜자가 따로 없이 누구나 생산 할 수 있고 모두가 손쉽게 공유하면서도 정체되지 않고 계속 진보하는, 집단지성의 특성을 보여준다. Google search 웹 페이지 평가에 다른 페이지에서 얼마나 링크를 많이 받았는지를 적용한 첫 검색 엔진이다. 수천 명이 특정 웹 페이지에 대해 말한 정보를 랭킹 방법에 적용하여 검 색 결과 순서를 정하는 데 이용했다. Web Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Collective Intelligence Benefits of collective intelligence Higher retention rates The more users interact with the application, the stickier it gets for them, and the higher the probability that they’ll become repeat visitors. Greater opportunities to market to the user The greater the number of interactions, the greater the number of pages visited by the user, which increases the opportunities to market to or communicate with the user Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Collective Intelligence Benefits of collective intelligence Higher probability of a user completing a transaction and finding information of interest The more contextually relevant information that a user finds, the better the chances that he’ll have the information he needs to complete the transaction or find content of interest. This leads to higher click-through and conversion rates for your advertisements. Boosting search engine rankings The more users participate and contribute content, the more content is available in your application and indexed by search engines. This could boost your search engine ranking and make it easier for others to find your application Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Collective Intelligence CI in web applications Three things that need to happen to apply collective intelligence in your application. Allow users to interact with your site and with each other, learning about each user through their interactions and contributions. Aggregate what you learn about your users and their contributions using some useful models. Leverage those models to recommend relevant content to a user Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Collective Intelligence CI in web applications Three components to harnessing collective intelligence. Allow users to interact. Learn about your users in aggregate. Personalize content using user interaction data and aggregate data Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Social Network By Yunfeng Pei

Social Network Concept Social Network 는 web science 의 연구 분야 중 하나로, web 상에서 개인 또는 집단이 하나의 노드 (node) 가 되어 각 노드 들 간의 상호의 존적인 관계 (tie) 에 의해 만들어지는 사회적 관 계 구조를 말한다. Node 는 network 에서 존재하는 개별적인 주체들이다. Tie 는 각 node 들의 관계를 말한다 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Social Network Social network analysis - SNA Social network analysis 사람과 사람들 간의 중요한 지식관계 를 반영하며, 특별히 조직간의 협조를 향상시키고, 지식을 창 조하며, 지식을 전파한다. Social network analysis 는 수많은 노드들과 그 노드들 사이 의 무수히 다양한 관계들로 인해 계산론적으로 접근하기에 매 우 복잡한 분야이다. Social network analysis 는 현재 중요한 기술로 거듭나고 있 다. 그리고 또한 이슈되는 연구분야이다 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Social Network Social network analysis Solve some problems Choose a leader 어떠한 사람이 수많은 사람들 중에서 신뢰성이 높고 존경을 받는 것인가 ? Choose a task team 어떻게 하면 조직네에서 연결이 있는 사람들을 하나의 팀으로 조성하는가 ? Mergers & Acquisitions 두 문화가 합병되는 것만이 아니라, 두 독립적인 네트워크를 합병하는 것이다 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Social Network Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. An example of a social network diagram.

Social Network Social network analysis Betweenness A node lies between other nodes in the network. The connectivity of the node's neighbors. Giving a higher value for nodes which bridge clusters. Bridge An edge is said to be a bridge if deleting it would cause its endpoints to lie in different components of a graph Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Social Network Social network analysis Closeness The degree an individual is near all other individuals in a network. It reflects the ability to access information. Thus, closeness is the inverse of the sum of the shortest distances between each individual and every other person in the network Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Social Network Social network analysis Degree The count of the number of ties to other actors in the network. Network or global-level density is the proportion of ties in a network relative to the total number possible. The degree that a node contributes to sum of maximum flow between all pairs of nodes Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Social Network Social network analysis Centralization The difference between the number of links for each node divided by maximum possible sum of differences. A centralized network will have many of its links dispersed around one or a few nodes, while a decentralized network is one in which there is little variation between the number of links each node possesses Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Social Network Social network analysis Social network analysis software Network analytic tools are used to represent the nodes (agents) and edges (relationships) in a network, and to analyze the network data. Network analysis tools allow researchers to investigate large networks like the Internet, disease transmission, etc Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. The Semantic Web By Yunfeng Pei

The Semantic Web Concept The Semantic Web is an evolving development of the World Wide Web in which the meaning of information and services on the web is defined, making it possible for the web to "understand" and satisfy the requests of people and machines to use the web content Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

The Semantic Web The difference The world wide web Hypertext Markup Language (HTML). HTML 로 작성된 contents 는 컴퓨터가 해석할수 있는 meta data 보다는 사람의 시 각정보에 대한 meta data 와 자연어로 작성된 contents 로 되여있다. The semantic web Resource Description Framework (RDF), Web Ontology Language (OWL), Extensible Markup Language (XML). 이런 언어를 기반으로 작성된 contents 는 컴퓨터가 해석할수 있는 meta data 로 구 성 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

The Semantic Web Factor Ontology Ontology 는 일종의 지식표현으로서 컴퓨터를 하여끔 ontology 로 표현된 개념을 이해하고 지식처리를 할 수 있는것이다. agent 유저를 대신햐여 정보를 수집하고, 정보를 검색하며, ontology 를 이용하 여 다른 agent 과 교류하여 유저대신에 일상 일를 처리하는 것이다. agent 는 the semantic web 중에서 중요한 요소이다 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

The Semantic Web Components Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

The Semantic Web Components XML Extensible Markup Language. The language framework that has been used to define nearly all new languages that are used to interchange data over the web. XML Schema A language used to define the structure of specific XML languages. RDF A flexible language capable of describing all sorts of information and meta data Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

The Semantic Web Components RDF Schema A framework that provides a means to specify basic vocabularies for specific RDF application languages to use. RDF Schema is a framework for constructing ontologies and is used by many more advanced ontology frameworks. Ontology Languages used to define vocabularies and establish the usage of words and terms in the context of a specific vocabulary Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

The Semantic Web Components Logic and Proof Logical reasoning is used to establish the consistency and correctness of data sets and to infer conclusions that aren’t explicitly stated but are required by or consistent with a known set of data. Proofs trace or explain the steps of logical reasoning. Trust A means of providing authentication of identity and evidence of the trustworthiness of data, services, and agents Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

The Semantic Web Vision The semantic web is a vision of information that is understandable by computers, so that users can perform more of the tedious work involved in finding, combining, and acting upon information on the web Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

The Semantic Web Application RSS(RDF Site Summary) Web blog Portal Search Engine The semantic web service Business Intelligence Knowledge Management Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Ontology By Yunfeng Pei

Ontology Concept In theory Ontologies are defined as a formal specification of a shared conceptualization. In English An ontology provides a shared vocabulary, which can be used to model a domain, that is, the type of objects and/or concepts that exist, and their properties and relations Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Ontology Components Class sets, collections, concepts, classes in programming, types of objects, or kinds of things. Instances instances or objects Relation ways in which classes and individuals can be related to one another Property aspects, properties, features, characteristics, or parameters that objects (and classes) can have Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Ontology Ontology language RDF (Resource Description Framework) RDF is a standard model for data interchange on the Web. RDF has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed. OWL (Web Ontology Language) The W3C Web Ontology Language (OWL) is a Semantic Web language designed to represent rich and complex knowledge about things, groups of things, and relations between things Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Ontology Ontology language SWRL (Semantic Web Rule Language) SWRL is a proposal for a Semantic Web rules-language, combining sublanguages of the OWL Web Ontology Language (OWL DL and Lite) with those of the Rule Markup Language Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Ontology Perspectives Library and Information Science Artificial Intelligence Natural Language Processing The Semantic Web Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Ontology Artificial Intelligence Objectives Model common sense and domain knowlege Usage Knowledge representation and reasoning Examples CYC,… Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Ontology The Semantic Web Objectives Provide semantics for web resource Usage Describe resources and their contents Examples DC, DAML-library,… Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Ontology The Ontology Web Language – OWL Goal Formally describe the semantics of classes and properties used in web documents. Go beyond the basic semantics in RDFS Current status Use cases and their requirements on ontologies Eight design goals Requirements Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Ontology The Ontology Web Language – OWL Design goals Shared ontologies Ontology interoperability Inconsistency detection Balance of expressivity and scalability Ease of use XML syntax Internationalisation Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.

Ontology The Ontology Web Language – OWL Requirements Ontologies as distinct objects Unambiguous term referencing with URIs Explicit ontology extension Commitment to ontologies Ontology metadata Versioning information Class definition primitives Property definition primitives Datatypes Class and property equivalence Local unique names assumption Etc… Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ.