Building and Integrating Competitive Intelligence Reports Using the Topic Map Technology
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Building and Integrating Competitive Intelligence Reports Using the Topic Map Technology

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Competitive intelligence (CI) supports the decision makers in understanding the competitive environment by means of textual reports prepared based on public resources. CI is particularly demanding in ...

Competitive intelligence (CI) supports the decision makers in understanding the competitive environment by means of textual reports prepared based on public resources. CI is particularly demanding in the context of larger business
clusters. We report on a long-term project featuring large-scale manual semantic annotation of CI reports wrt. business clusters in several industries. The underlying ontologies are the result of collaborative editing by multiple student teams. The results of annotation are finally merged into CI maps that allow easy access to both the original documents and the knowledge structures.

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    Building and Integrating Competitive Intelligence Reports Using the Topic Map Technology Building and Integrating Competitive Intelligence Reports Using the Topic Map Technology Presentation Transcript

    • Building and Integrating Competitive IntelligenceReports Using the Topic Map Technology
      Vojtěch Svátek, Tomáš Kliegr, Jan Nemrava, Martin Ralbovsý,
      Vojtěch Roček ,Jan Rauch
      University of Economics, Winston Churchill Sq. 4, Prague, Czech Republic
      Jiří Šplíchal, Tomáš Vejlupek
      Tovek s.r.o., Chrudimská 1418, Prague, Czech Republic
    • CI and Business Clusters
      CI – Competitive Intelligence is a sub-field of business intelligence that supports decision makers in understanding the competitive environment by means of reports prepared based on (public) resources.
      Cluster is a set of companies in related fields operating in the same geographical area
      How to link and search
      multiple CI reports?
      Envisaged Solution: Create a complementary topic map
      that would put the important facts into context
    • TheTopic Map
      1] Ontology: putting concepts into context
      Instances
      Associations
      TopicTypes
      2] Annotate important bits of text with ontology concepts
    • Testbed
      A case study assignment at an introductory knowledge engineering course, attended by 150- 200 students each semester
      The goal is to get a picture of the whole industry
      Students work in groups of 5
      • Each group covers one company and its environment
      Two assignments:
      Students write CI reports of about 25 pages based on publicly available sources of information.
      2) Important pieces of information are expressed in a machine-readable way with topic maps.
      Each semester we tested a slightly different setting (S1-S3) of tools and techniques… now running for the fourth semester
    • S1: Individual ontologies, merge
      Each team wrote the CI report (in a text editor)
      Consequently, they obtained a copy of a startup ontology
      Students extended the ontology with new topic types using Tovek Topic Mapper (TTM): an ontology editor and annotating tool (desktop application)
      Students used TTM to annotate bits of text with a topic type.
      Annotated text became an internal occurrence in the topic map
      The ontologies enriched with new topic types and annotations were collected from all teams
      We used OKS to merge the topic maps
      Extend ontology
      Annotate
      DOC
      HTML
      The result is a linking file between the document and the shared topic map
      XTM
      Startup Ontology
      Result is a linking file conneting document with the topic map
    • Topic Maps Merging
      Merging of: Business cluster topic map, All unstructured documents, Linking files
      Linking files
      CI reports
      HTML
      XTM
      DOC
      Shared industry topic map
    • Issues
      Annotated text fragmented, since each fragment is stored as internal occurrence
      Laborious
      Duplicate topic types
      Effective merging requires unique identifiers, which was achieved only for companies (registration numbers used in subject indicators)
    • S2: Collaborative Ontology Population
      Goal: remove duplicate topic types
      Startup ontology was placed on a PostgreSQL server
      Student teams collaboratively enriched the ontology with topic types, association types and occurrence types they assumed to use during the annotation in Topic Mapper
      The ontology was then frozen: each team got its copy.
      TTM was used only for annotation, and then OKS for merging
      Collaborative Ontology Creation
      remote repository
      Topic Maps
      for
      Merging
      Import
      ontology
      Shared topic map
      students
      Annotate only
    • Issues
      Separation of ontology enrichment and document annotation is not natural and requires an experienced annotator
      Annotations still kept as internal occurrences
      Multiple concurrent instances of OKS servers resulted in corruption in the topic map, probably due to caching in OKS
      Two topic map tools used, original documents not easily accessible
    • S3: Annotation by linking
      Goal: move annotation fully to the web
      All students used one instance of OKS server
      CI reports were placed into a CMS (Joomla!)
      Each structural unit was assigned an id (via HTML’s <a name>)
      Annotation was done via external occurrences
      External occurrences point at a specific bookmark at the document, where the annotated fragment starts. The annotated fragment is assumed to span up to the nearest following bookmark.
    • Issues … and finally advantages
      Issues:
      OKS Ontopoly was not stable enough in concurrent setting
      X-Pointer technology, which could be used to mark spans in the document, is not supported by current browsers
      Advantages:
      The text with full content (including even figures or links) in the CMS is more intelligible than fragments in internal occurrences
      Further editing of an article is possible in the CMS without invalidating the annotation
      Full-text search feature of the CMS can be exploited
      Bringing the best from the CMS world and OKS
    • Summary& Plans
      On the competitive intelligence use case, we tested several approaches for collaborative ontology design and document annotation with some 500 users altogether.
      OKS is a great tool, which gets additional edge by being web-based
      We deem the last approach taken: documents stored in a CMS linked through external occurrences with OKS as usable - contingent on improvements in Ontopoly and Joomla!
      Ontopoly wishes
      Greater stability in case of concurrent user access
      We missed user management and versioning in Ontopoly
      Joomla! wishes
      Support for „tagging“ arbitrary bits of text
      A tool for creating XPointer URLs based on user selection
      A functionality that would highlight part of the document based on a URL containing XPointer span