WELCOME!
WELCOME! Chapter 7
WELCOME! Chapter 7
WELCOME! Chapter 7 KNOWLEDGE MANAGEMENT TOOLS:
WELCOME! Chapter 7 KNOWLEDGE MANAGEMENT TOOLS: Component Technologies
LEARNING OBJECTIVES
LEARNING OBJECTIVES To explain the differences between ontology and taxonomy tools for organising knowledge
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
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
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
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
BUZZ GROUP
BUZZ GROUP What types of knowledge or information do I use in my everyday life?
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
Figure 7.1 A typology of knowledge tools and component technologies
COMPONENT TOOLS TYPOLOGY Figure 7.1 A typology of knowledge tools and component technologies
Figure 7.2 Different forms of knowledge
DIFFERENT FORMS OF KNOWLEDGE Figure 7.2 Different forms of knowledge
Figure 7.3 Ontology and taxonomies
ORGANISING KNOWLEDGE: ONTOLOGY & TAXONOMY Figure 7.3 Ontology and taxonomies
ONTOLOGY GENERATION TECHNOLOGIES
Manually ONTOLOGY GENERATION TECHNOLOGIES
ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging
ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging Word sense disambiguation
ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging Word sense disambiguation Tokeniser
ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging Word sense disambiguation Tokeniser Pattern matching
ONTOLOGY GENERATION TECHNOLOGIES Manually Part of speech tagging Word sense disambiguation Tokeniser Pattern matching Semi-automatic generation with machine learning
BUZZ GROUPS
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
Figure 7.4 Ontology integration techniques
INTEGRATING ONTOLOGIES (see Ding & Foo, 2002) Figure 7.4 Ontology integration techniques
CAPTURING KNOWLEDGE Cognitive Mapping Tools
CAPTURING KNOWLEDGE Cognitive Mapping Tools Used principally in mapping strategic knowledge
CAPTURING KNOWLEDGE Cognitive Mapping Tools Used principally in mapping strategic knowledge Use oval mapping technique in groups
CAPTURING KNOWLEDGE Cognitive Mapping Tools Used principally in mapping strategic knowledge Use oval mapping technique in groups Develop concepts, links and clusters
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
Figure 7.8 Indexing a text database
CAPTURING KNOWLEDGE Indexing a Text Database Figure 7.8 Indexing a text database
CAPTURING KNOWLEDGE Information Retrieval Tools
CAPTURING KNOWLEDGE Information Retrieval Tools Desire for precision and recall
CAPTURING KNOWLEDGE Information Retrieval Tools Desire for precision and recall Differences between an author s and user s vocabulary
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
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
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
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
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
Figure 7.9 Information retrieval process
CAPTURING KNOWLEDGE Retrieval Process Figure 7.9 Information retrieval process
CAPTURING KNOWLEDGE Text Processing
CAPTURING KNOWLEDGE Text Processing Lexical analysis to identify words from characters
CAPTURING KNOWLEDGE Text Processing Lexical analysis to identify words from characters Eliminating stopwords occurring frequently
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
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
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
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
Figure 7.10 Search engine: crawler-indexer architecture
CAPTURING KNOWLEDGE Search Engines: Crawler Indexer Figure 7.10 Search engine: crawler-indexer architecture
CAPTURING KNOWLEDGE Search Engines: IR and the Web
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
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
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
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
CAPTURING KNOWLEDGE Personalisation
CAPTURING KNOWLEDGE Personalisation Device provides needs and wants of consumer
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
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
EVALUATING KNOWLEDGE Case-based reasoning
EVALUATING KNOWLEDGE Case-based reasoning Capture and store past experiences as organisational knowledge
EVALUATING KNOWLEDGE Case-based reasoning Capture and store past experiences as organisational knowledge System searches for stored cases with similar profile to new problem
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
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
BUZZ GROUPS
BUZZ GROUPS Discuss the limitations of case-based reasoning tools
EVALUATING KNOWLEDGE OLAP: On-line analytical processing
EVALUATING KNOWLEDGE OLAP: On-line analytical processing Provides multidimensional analysis of data to allow user to see data in different ways using multiple dimensions
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
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
EVALUATING KNOWLEDGE Data mining
EVALUATING KNOWLEDGE Data mining Uses variety of neural network, decision trees and genetic modeling algorithms
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
SHARING KNOWLEDGE Internet/Intranet
SHARING KNOWLEDGE Internet/Intranet Share knowledge with knowledge providers across the world some free
SHARING KNOWLEDGE Internet/Intranet Share knowledge with knowledge providers across the world some free Intranet provides same but restricted access from outside
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
BUZZ GROUPS Intranets can be large data warehouses that nobody visits. Critically discuss the barriers that prevent knowledge sharing in organisations
SHARING KNOWLEDGE Groupware tools
SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users
SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users Maintain and update identical data on numerous PCs
SHARING KNOWLEDGE Groupware tools Allows to work on same document by multiple users Maintain and update identical data on numerous PCs Organising discussions
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
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
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
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
SHARING KNOWLEDGE
SHARING KNOWLEDGE E-mail
SHARING KNOWLEDGE E-mail Text-based conferencing
SHARING KNOWLEDGE E-mail Text-based conferencing Yellow Pages
SHARING KNOWLEDGE E-mail Text-based conferencing Yellow Pages Computer-based training/e-learning
SHARING KNOWLEDGE E-mail Text-based conferencing Yellow Pages Computer-based training/e-learning Security
WEB 2.0 PLATFORM
WEB 2.0 PLATFORM Shift to dynamic social web applications
WEB 2.0 PLATFORM Shift to dynamic social web applications Network effects critical to their success
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)
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
TIPPING POINT WORD OF MOUTH EPIDEMICS
TIPPING POINT WORD OF MOUTH EPIDEMICS Connectors social glue
TIPPING POINT WORD OF MOUTH EPIDEMICS Connectors social glue Mavens information brokers on best deals etc.
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
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
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
WEB 2.0 PLATFORM Figure 7.11 Web 2.0 platform tools
BLOGS
BLOGS Blogs adding thoughts or diary of events
BLOGS Blogs adding thoughts or diary of events Podcasts audio blogs
BLOGS Blogs adding thoughts or diary of events Podcasts audio blogs Vlog video blog
BLOGS Blogs adding thoughts or diary of events Podcasts audio blogs Vlog video blog Trackbacks allows bloggers to see who s linking to them
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
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
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
SYNDICATION & RSS FEEDS
SYNDICATION & RSS FEEDS Information from articles and photos repackaged for different customers
SYNDICATION & RSS FEEDS Information from articles and photos repackaged for different customers RSS (Really Simple Syndication) format to publish frequently updated content on websites
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
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
MASHUPS
MASHUPS Allows content from different sources to combine with applications for different business processes
MASHUPS Allows content from different sources to combine with applications for different business processes E.g. Getting insurance quote from website
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
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
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
WIKIS
WIKIS Web pages that can be viewed and modified by anyone
WIKIS Web pages that can be viewed and modified by anyone Allows to create or change web content
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
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
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
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
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
ONLINE SOCIAL NETWORKS
ONLINE SOCIAL NETWORKS Individuals interact with others in community
ONLINE SOCIAL NETWORKS Individuals interact with others in community Social network sites (SNS): Facebook, MySpace, LinkedIn, Friendster
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
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
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
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
3-D VIRTUAL WORLDS
3-D VIRTUAL WORLDS Computer-simulated worlds where users interact in real time through avatars
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
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$)
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$) Conduct meetings, workshops and recruitment
3-D VIRTUAL WORLDS Computer-simulated worlds where users interact in real time through avatars Avatars are 3-D electronic cartoons of users; form of alter ego Second Life has over 15m users and internal currency of Linden dollars (L$) Conduct meetings, workshops and recruitment Multinationals such as IBM, Dell, Ericsson, Bain
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
STORING KNOWLEDGE Data Warehouse
STORING KNOWLEDGE Data Warehouse Database with query and reporting tools
STORING KNOWLEDGE Data Warehouse Database with query and reporting tools Stores current and historical data from internal and external sources
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
PRESENTING KNOWLEDGE Visualisation
PRESENTING KNOWLEDGE Visualisation Modelling way of representing objects e.g. journal covers, weather maps, flows of citations
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
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