Slide 7. Jashapara, Knowledge Management: An Integrated Approach, 2 nd Edition, Pearson Education Limited Nisan 14 Pazartesi
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1
2 WELCOME!
3 WELCOME! Chapter 7
4 WELCOME! Chapter 7
5 WELCOME! Chapter 7 KNOWLEDGE MANAGEMENT TOOLS:
6 WELCOME! Chapter 7 KNOWLEDGE MANAGEMENT TOOLS: Component Technologies
7 LEARNING OBJECTIVES
8 LEARNING OBJECTIVES To explain the differences between ontology and taxonomy tools for organising knowledge
9 LEARNING OBJECTIVES To explain the differences between ontology and taxonomy tools for organising knowledge To describe cognitive mapping and information retrieval tools for capturing knowledge
10 LEARNING OBJECTIVES To explain the differences between ontology and taxonomy tools for organising knowledge To describe cognitive mapping and information retrieval tools for capturing knowledge To distinguish between different tools for evaluating knowledge
11 LEARNING OBJECTIVES To explain the differences between ontology and taxonomy tools for organising knowledge To describe cognitive mapping and information retrieval tools for capturing knowledge To distinguish between different tools for evaluating knowledge To assess the different tools for sharing knowledge
12 LEARNING OBJECTIVES To explain the differences between ontology and taxonomy tools for organising knowledge To describe cognitive mapping and information retrieval tools for capturing knowledge To distinguish between different tools for evaluating knowledge To assess the different tools for sharing knowledge To explain technologies for storing and presenting knowledge
13
14 BUZZ GROUP
15 BUZZ GROUP What types of knowledge or information do I use in my everyday life?
16 BUZZ GROUP What types of knowledge or information do I use in my everyday life? What types of technology do I use to manage this knowledge? You may wish to consider the types of technologies you use to capture, organise, evaluate, store and share knowledge
17 Figure 7.1 A typology of knowledge tools and component technologies
18 COMPONENT TOOLS TYPOLOGY Figure 7.1 A typology of knowledge tools and component technologies
19 Figure 7.2 Different forms of knowledge
20 DIFFERENT FORMS OF KNOWLEDGE Figure 7.2 Different forms of knowledge
21 Figure 7.3 Ontology and taxonomies
22 ORGANISING KNOWLEDGE: ONTOLOGY & TAXONOMY Figure 7.3 Ontology and taxonomies
23
24 ONTOLOGY GENERATION TECHNOLOGIES
25 Manually ONTOLOGY GENERATION TECHNOLOGIES
26 ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging
27 ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging Word sense disambiguation
28 ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging Word sense disambiguation Tokeniser
29 ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging Word sense disambiguation Tokeniser Pattern matching
30 ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging Word sense disambiguation Tokeniser Pattern matching Semi-automatic generation with machine learning
31 BUZZ GROUPS
32 BUZZ GROUPS Describe the different options available to you for integrating ontologies from two distinct knowledge bases in the organisation such as sales and finance. This could equally apply to integrating knowledge bases between two organisations in a takeover or merger situation
33 Figure 7.4 Ontology integration techniques
34 INTEGRATING ONTOLOGIES (see Ding & Foo, 2002) Figure 7.4 Ontology integration techniques
35 CAPTURING KNOWLEDGE Cognitive Mapping Tools
36 CAPTURING KNOWLEDGE Cognitive Mapping Tools Used principally in mapping strategic knowledge
37 CAPTURING KNOWLEDGE Cognitive Mapping Tools Used principally in mapping strategic knowledge Use oval mapping technique in groups
38 CAPTURING KNOWLEDGE Cognitive Mapping Tools Used principally in mapping strategic knowledge Use oval mapping technique in groups Develop concepts, links and clusters
39 CAPTURING KNOWLEDGE Cognitive Mapping Tools Used principally in mapping strategic knowledge Use oval mapping technique in groups Develop concepts, links and clusters Decision Explorer can develop complex levels of analysis
40 Figure 7.8 Indexing a text database
41 CAPTURING KNOWLEDGE Indexing a Text Database Figure 7.8 Indexing a text database
42 CAPTURING KNOWLEDGE Information Retrieval Tools
43 CAPTURING KNOWLEDGE Information Retrieval Tools Desire for precision and recall
44 CAPTURING KNOWLEDGE Information Retrieval Tools Desire for precision and recall Differences between an author s and user s vocabulary
45 CAPTURING KNOWLEDGE Information Retrieval Tools Desire for precision and recall Differences between an author s and user s vocabulary Use of inverted files for indexing text to speed up search assumes text as sequence of words easy to compress
46 CAPTURING KNOWLEDGE Information Retrieval Tools Desire for precision and recall Differences between an author s and user s vocabulary Use of inverted files for indexing text to speed up search assumes text as sequence of words easy to compress Develop inverted index including vocabulary search, list of occurrences and processing of occurrences to solve phrases, proximity and Boolean operations
47 CAPTURING KNOWLEDGE Information Retrieval Tools Desire for precision and recall Differences between an author s and user s vocabulary Use of inverted files for indexing text to speed up search assumes text as sequence of words easy to compress Develop inverted index including vocabulary search, list of occurrences and processing of occurrences to solve phrases, proximity and Boolean operations Suffix Trees & Indicies allows more complex queries. Sees text as long string with each position as a suffix
48 CAPTURING KNOWLEDGE Information Retrieval Tools Desire for precision and recall Differences between an author s and user s vocabulary Use of inverted files for indexing text to speed up search assumes text as sequence of words easy to compress Develop inverted index including vocabulary search, list of occurrences and processing of occurrences to solve phrases, proximity and Boolean operations Suffix Trees & Indicies allows more complex queries. Sees text as long string with each position as a suffix Signature files cuts text into blocks. Not as good as inverted index
49 CAPTURING KNOWLEDGE Information Retrieval Tools Desire for precision and recall Differences between an author s and user s vocabulary Use of inverted files for indexing text to speed up search assumes text as sequence of words easy to compress Develop inverted index including vocabulary search, list of occurrences and processing of occurrences to solve phrases, proximity and Boolean operations Suffix Trees & Indicies allows more complex queries. Sees text as long string with each position as a suffix Signature files cuts text into blocks. Not as good as inverted index Manipulation algorithms such as BNDM and BMS for Boolean queries
50 Figure 7.9 Information retrieval process
51 CAPTURING KNOWLEDGE Retrieval Process Figure 7.9 Information retrieval process
52
53 CAPTURING KNOWLEDGE Text Processing
54 CAPTURING KNOWLEDGE Text Processing Lexical analysis to identify words from characters
55 CAPTURING KNOWLEDGE Text Processing Lexical analysis to identify words from characters Eliminating stopwords occurring frequently
56 CAPTURING KNOWLEDGE Text Processing Lexical analysis to identify words from characters Eliminating stopwords occurring frequently Stemming e.g. Connect is stem for connected, connecting, and connections
57 CAPTURING KNOWLEDGE Text Processing Lexical analysis to identify words from characters Eliminating stopwords occurring frequently Stemming e.g. Connect is stem for connected, connecting, and connections Full text indexing
58 CAPTURING KNOWLEDGE Text Processing Lexical analysis to identify words from characters Eliminating stopwords occurring frequently Stemming e.g. Connect is stem for connected, connecting, and connections Full text indexing Thesaurus index terms synonyms and near synonyms
59 CAPTURING KNOWLEDGE Text Processing Lexical analysis to identify words from characters Eliminating stopwords occurring frequently Stemming e.g. Connect is stem for connected, connecting, and connections Full text indexing Thesaurus index terms synonyms and near synonyms Text compression to cope with information overload
60 Figure 7.10 Search engine: crawler-indexer architecture
61 CAPTURING KNOWLEDGE Search Engines: Crawler Indexer Figure 7.10 Search engine: crawler-indexer architecture
62 CAPTURING KNOWLEDGE Search Engines: IR and the Web
63 CAPTURING KNOWLEDGE Search Engines: IR and the Web Centralised crawler-indexer architecture. Crawlers (software agents) traverse web sending back pages for indexing. Indexer deals with query from user and new info. from crawler
64 CAPTURING KNOWLEDGE Search Engines: IR and the Web Centralised crawler-indexer architecture. Crawlers (software agents) traverse web sending back pages for indexing. Indexer deals with query from user and new info. from crawler Decentralised gatherers-brokers architecture. Gatherers collect and extract indexing info. from lots of servers. Brokers provide indexing and query interface
65 CAPTURING KNOWLEDGE Search Engines: IR and the Web Centralised crawler-indexer architecture. Crawlers (software agents) traverse web sending back pages for indexing. Indexer deals with query from user and new info. from crawler Decentralised gatherers-brokers architecture. Gatherers collect and extract indexing info. from lots of servers. Brokers provide indexing and query interface Metasearchers are Web servers that send query to several search engines
66 CAPTURING KNOWLEDGE Search Engines: IR and the Web Centralised crawler-indexer architecture. Crawlers (software agents) traverse web sending back pages for indexing. Indexer deals with query from user and new info. from crawler Decentralised gatherers-brokers architecture. Gatherers collect and extract indexing info. from lots of servers. Brokers provide indexing and query interface Metasearchers are Web servers that send query to several search engines Most common query on the Web is 2.3 words
67
68 CAPTURING KNOWLEDGE Personalisation
69 CAPTURING KNOWLEDGE Personalisation Device provides needs and wants of consumer
70 CAPTURING KNOWLEDGE Personalisation Device provides needs and wants of consumer Solution lies in data mining in terms of analysing user s clickstream and making recommendations
71 CAPTURING KNOWLEDGE Personalisation Device provides needs and wants of consumer Solution lies in data mining in terms of analysing user s clickstream and making recommendations Use of agents and machine learning
72
73 EVALUATING KNOWLEDGE Case-based reasoning
74 EVALUATING KNOWLEDGE Case-based reasoning Capture and store past experiences as organisational knowledge
75 EVALUATING KNOWLEDGE Case-based reasoning Capture and store past experiences as organisational knowledge System searches for stored cases with similar profile to new problem
76 EVALUATING KNOWLEDGE Case-based reasoning Capture and store past experiences as organisational knowledge System searches for stored cases with similar profile to new problem Adds unsuccessful cases to aid learning
77 EVALUATING KNOWLEDGE Case-based reasoning Capture and store past experiences as organisational knowledge System searches for stored cases with similar profile to new problem Adds unsuccessful cases to aid learning Built on artificial intelligence technology
78 BUZZ GROUPS
79 BUZZ GROUPS Discuss the limitations of case-based reasoning tools
80
81 EVALUATING KNOWLEDGE OLAP: On-line analytical processing
82 EVALUATING KNOWLEDGE OLAP: On-line analytical processing Provides multidimensional analysis of data to allow user to see data in different ways using multiple dimensions
83 EVALUATING KNOWLEDGE OLAP: On-line analytical processing Provides multidimensional analysis of data to allow user to see data in different ways using multiple dimensions Main technique is to rotate a data cube
84 EVALUATING KNOWLEDGE OLAP: On-line analytical processing Provides multidimensional analysis of data to allow user to see data in different ways using multiple dimensions Main technique is to rotate a data cube Also called slice and dice
85
86 EVALUATING KNOWLEDGE Data mining
87 EVALUATING KNOWLEDGE Data mining Uses variety of neural network, decision trees and genetic modeling algorithms
88 EVALUATING KNOWLEDGE Data mining Uses variety of neural network, decision trees and genetic modeling algorithms Use sophisticated data search capabilities using algorithms to discover patterns and correlations in vast amounts of data
89 SHARING KNOWLEDGE Internet/Intranet
90 SHARING KNOWLEDGE Internet/Intranet Share knowledge with knowledge providers across the world some free
91 SHARING KNOWLEDGE Internet/Intranet Share knowledge with knowledge providers across the world some free Intranet provides same but restricted access from outside
92 SHARING KNOWLEDGE Internet/Intranet Share knowledge with knowledge providers across the world some free Intranet provides same but restricted access from outside Uses HTML and XML a metalanguage that allows definition of tags and allows distribution of knowledge to call phones, pagers and PDAs
93 BUZZ GROUPS Intranets can be large data warehouses that nobody visits. Critically discuss the barriers that prevent knowledge sharing in organisations
94
95 SHARING KNOWLEDGE Groupware tools
96 SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users
97 SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users Maintain and update identical data on numerous PCs
98 SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users Maintain and update identical data on numerous PCs Organising discussions
99 SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users Maintain and update identical data on numerous PCs Organising discussions Storing information
100 SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users Maintain and update identical data on numerous PCs Organising discussions Storing information Moving and tracking documents of groups
101 SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users Maintain and update identical data on numerous PCs Organising discussions Storing information Moving and tracking documents of groups Preventing unauthorised access of data
102 SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users Maintain and update identical data on numerous PCs Organising discussions Storing information Moving and tracking documents of groups Preventing unauthorised access of data Mobile use to access corporate network
103
104 SHARING KNOWLEDGE
105 SHARING KNOWLEDGE
106 SHARING KNOWLEDGE Text-based conferencing
107 SHARING KNOWLEDGE Text-based conferencing Yellow Pages
108 SHARING KNOWLEDGE Text-based conferencing Yellow Pages Computer-based training/e-learning
109 SHARING KNOWLEDGE Text-based conferencing Yellow Pages Computer-based training/e-learning Security
110 WEB 2.0 PLATFORM
111 WEB 2.0 PLATFORM Shift to dynamic social web applications
112 WEB 2.0 PLATFORM Shift to dynamic social web applications Network effects critical to their success
113 WEB 2.0 PLATFORM Shift to dynamic social web applications Network effects critical to their success Provide customer services free Google ($200bn), YouTube ($1.6bn), Facebook ($50bn)
114 WEB 2.0 PLATFORM Shift to dynamic social web applications Network effects critical to their success Provide customer services free Google ($200bn), YouTube ($1.6bn), Facebook ($50bn) Indirect network effects from use of products or services that have influence on related goods and services
115 TIPPING POINT WORD OF MOUTH EPIDEMICS
116 TIPPING POINT WORD OF MOUTH EPIDEMICS Connectors social glue
117 TIPPING POINT WORD OF MOUTH EPIDEMICS Connectors social glue Mavens information brokers on best deals etc.
118 TIPPING POINT WORD OF MOUTH EPIDEMICS Connectors social glue Mavens information brokers on best deals etc. Salesmen good at convincing you and getting you to act
119 TIPPING POINT WORD OF MOUTH EPIDEMICS Connectors social glue Mavens information brokers on best deals etc. Salesmen good at convincing you and getting you to act Amazon is reliant on ranking of reviewers to develop trust with customers
120 TIPPING POINT WORD OF MOUTH EPIDEMICS Connectors social glue Mavens information brokers on best deals etc. Salesmen good at convincing you and getting you to act Amazon is reliant on ranking of reviewers to develop trust with customers Six degrees of separation
121 WEB 2.0 PLATFORM Figure 7.11 Web 2.0 platform tools
122 BLOGS
123 BLOGS Blogs adding thoughts or diary of events
124 BLOGS Blogs adding thoughts or diary of events Podcasts audio blogs
125 BLOGS Blogs adding thoughts or diary of events Podcasts audio blogs Vlog video blog
126 BLOGS Blogs adding thoughts or diary of events Podcasts audio blogs Vlog video blog Trackbacks allows bloggers to see who s linking to them
127 BLOGS Blogs adding thoughts or diary of events Podcasts audio blogs Vlog video blog Trackbacks allows bloggers to see who s linking to them Can act as alternative to face-to-face meetings to engage in problem solving
128 BLOGS Blogs adding thoughts or diary of events Podcasts audio blogs Vlog video blog Trackbacks allows bloggers to see who s linking to them Can act as alternative to face-to-face meetings to engage in problem solving Engage with customers across boundaries
129 BLOGS Blogs adding thoughts or diary of events Podcasts audio blogs Vlog video blog Trackbacks allows bloggers to see who s linking to them Can act as alternative to face-to-face meetings to engage in problem solving Engage with customers across boundaries Twitter micro-blogging site
130 SYNDICATION & RSS FEEDS
131 SYNDICATION & RSS FEEDS Information from articles and photos repackaged for different customers
132 SYNDICATION & RSS FEEDS Information from articles and photos repackaged for different customers RSS (Really Simple Syndication) format to publish frequently updated content on websites
133 SYNDICATION & RSS FEEDS Information from articles and photos repackaged for different customers RSS (Really Simple Syndication) format to publish frequently updated content on websites Organisations can place feeds showing latest offerings or consumer information such as traffic news or weather forecasts
134 SYNDICATION & RSS FEEDS Information from articles and photos repackaged for different customers RSS (Really Simple Syndication) format to publish frequently updated content on websites Organisations can place feeds showing latest offerings or consumer information such as traffic news or weather forecasts RSS viral distribution engine for bloggers receive new material posted by favourite bloggers
135 MASHUPS
136 MASHUPS Allows content from different sources to combine with applications for different business processes
137 MASHUPS Allows content from different sources to combine with applications for different business processes E.g. Getting insurance quote from website
138 MASHUPS Allows content from different sources to combine with applications for different business processes E.g. Getting insurance quote from website E.g. Starbucks helps customers locate nearest café once they ve entered postcode
139 MASHUPS Allows content from different sources to combine with applications for different business processes E.g. Getting insurance quote from website E.g. Starbucks helps customers locate nearest café once they ve entered postcode Information from external sources can be inaccurate or may change significantly in future; even close down
140 MASHUPS Allows content from different sources to combine with applications for different business processes E.g. Getting insurance quote from website E.g. Starbucks helps customers locate nearest café once they ve entered postcode Information from external sources can be inaccurate or may change significantly in future; even close down Prone to threats from malware
141 WIKIS
142 WIKIS Web pages that can be viewed and modified by anyone
143 WIKIS Web pages that can be viewed and modified by anyone Allows to create or change web content
144 WIKIS Web pages that can be viewed and modified by anyone Allows to create or change web content Places power and freedom in hands of users rather than external expert
145 WIKIS Web pages that can be viewed and modified by anyone Allows to create or change web content Places power and freedom in hands of users rather than external expert Works in progress on virtual white boards
146 WIKIS Web pages that can be viewed and modified by anyone Allows to create or change web content Places power and freedom in hands of users rather than external expert Works in progress on virtual white boards Agendas and minutes can be placed on wikis
147 WIKIS Web pages that can be viewed and modified by anyone Allows to create or change web content Places power and freedom in hands of users rather than external expert Works in progress on virtual white boards Agendas and minutes can be placed on wikis Can be open to manipulation and vandalism
148 WIKIS Web pages that can be viewed and modified by anyone Allows to create or change web content Places power and freedom in hands of users rather than external expert Works in progress on virtual white boards Agendas and minutes can be placed on wikis Can be open to manipulation and vandalism Maintenance can be time-consuming
149 ONLINE SOCIAL NETWORKS
150 ONLINE SOCIAL NETWORKS Individuals interact with others in community
151 ONLINE SOCIAL NETWORKS Individuals interact with others in community Social network sites (SNS): Facebook, MySpace, LinkedIn, Friendster
152 ONLINE SOCIAL NETWORKS Individuals interact with others in community Social network sites (SNS): Facebook, MySpace, LinkedIn, Friendster SNS tend to support pre-existing relationships rather than new ones
153 ONLINE SOCIAL NETWORKS Individuals interact with others in community Social network sites (SNS): Facebook, MySpace, LinkedIn, Friendster SNS tend to support pre-existing relationships rather than new ones Benefit from social capital and self-presentation
154 ONLINE SOCIAL NETWORKS Individuals interact with others in community Social network sites (SNS): Facebook, MySpace, LinkedIn, Friendster SNS tend to support pre-existing relationships rather than new ones Benefit from social capital and self-presentation Risk over privacy from third party securing personal information
155 ONLINE SOCIAL NETWORKS Individuals interact with others in community Social network sites (SNS): Facebook, MySpace, LinkedIn, Friendster SNS tend to support pre-existing relationships rather than new ones Benefit from social capital and self-presentation Risk over privacy from third party securing personal information Allows interaction with different people in network
156 3-D VIRTUAL WORLDS
157 3-D VIRTUAL WORLDS Computer-simulated worlds where users interact in real time through avatars
158 3-D VIRTUAL WORLDS Computer-simulated worlds where users interact in real time through avatars Avatars are 3-D electronic cartoons of users; form of alter ego
159 3-D VIRTUAL WORLDS Computer-simulated worlds where users interact in real time through avatars Avatars are 3-D electronic cartoons of users; form of alter ego Second Life has over 15m users and internal currency of Linden dollars (L$)
160 3-D VIRTUAL WORLDS Computer-simulated worlds where users interact in real time through avatars Avatars are 3-D electronic cartoons of users; form of alter ego Second Life has over 15m users and internal currency of Linden dollars (L$) Conduct meetings, workshops and recruitment
161 3-D VIRTUAL WORLDS Computer-simulated worlds where users interact in real time through avatars Avatars are 3-D electronic cartoons of users; form of alter ego Second Life has over 15m users and internal currency of Linden dollars (L$) Conduct meetings, workshops and recruitment Multinationals such as IBM, Dell, Ericsson, Bain
162 3-D VIRTUAL WORLDS Computer-simulated worlds where users interact in real time through avatars Avatars are 3-D electronic cartoons of users; form of alter ego Second Life has over 15m users and internal currency of Linden dollars (L$) Conduct meetings, workshops and recruitment Multinationals such as IBM, Dell, Ericsson, Bain Strathclyde and Coventry Universities bought islands
163
164 STORING KNOWLEDGE Data Warehouse
165 STORING KNOWLEDGE Data Warehouse Database with query and reporting tools
166 STORING KNOWLEDGE Data Warehouse Database with query and reporting tools Stores current and historical data from internal and external sources
167 STORING KNOWLEDGE Data Warehouse Database with query and reporting tools Stores current and historical data from internal and external sources Data mart subset of data warehouse which contains summarised or highly focused data for certain users
168
169 PRESENTING KNOWLEDGE Visualisation
170 PRESENTING KNOWLEDGE Visualisation Modelling way of representing objects e.g. journal covers, weather maps, flows of citations
171 PRESENTING KNOWLEDGE Visualisation Modelling way of representing objects e.g. journal covers, weather maps, flows of citations Rendering makes computer generated image look like photograph e.g. texture mapping
172 PRESENTING KNOWLEDGE Visualisation Modelling way of representing objects e.g. journal covers, weather maps, flows of citations Rendering makes computer generated image look like photograph e.g. texture mapping Virtual reality
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