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Building a Top Down Ontology From the Bottom Up Step by Step Approach for Identifying & Constructing Dimensions of an Ontology draft (v0.8): DeniseBedford.

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Presentation on theme: "Building a Top Down Ontology From the Bottom Up Step by Step Approach for Identifying & Constructing Dimensions of an Ontology draft (v0.8): DeniseBedford."— Presentation transcript:

1 Building a Top Down Ontology From the Bottom Up Step by Step Approach for Identifying & Constructing Dimensions of an Ontology draft (v0.8): DeniseBedford /

2 Step by Step Approach Step 1: Identify the boundaries of the ontology –What will be ontologized (broad definition of content)? –Who will use the ontology? –How they will use the ontology? Following steps pertain to creating one dimension of an ontology to apply to content -- Step 2: Create a content inventory –Identify the sources of content –Use an inventory tool (COAST) to generate a full inventory –Working group weeds/selects from the inventory to create a core set of content to work with Step 3. Extract list of concepts from the content –Use the inventory to capture content items as a training set –Identify the types of concepts to be extracted – noun-phrase descriptors, entity identifiers, names, institutions, etc. –Configure and run the concept extraction

3 Step by Step Approach Step 4. Review the list of concepts –Quickly scan the concept list to determine concentrations of concepts –Check whether these concentrations make sense in terms of categories –If so, begin to build a categorization profile and organize the concepts within –Determine whats missing from the list of concepts (domain experts help us here..) –Determine what is in the list that is not pertinent to the topic (peripheral or out of bounds for the topic) – (domain experts here us here, too) –Prune the list of concepts – in some cases find new content and repeat the process Step 5x. Build the categorizer profile –Build a rule-based categorizer around the concept clusters (manual bunching at a very coarse level) –Or,…check clustering of concepts using a clustering engine (here you can feed the refined list of concepts back into a clustering engine and run them against the training set)

4 Questions for Domain Expert Review 1.If you were talking about ontology with an expert, are all of the concepts you would use included in the list? If not, what is missing? 1.Are there a few concepts missing, or is there a larger domain or knowledge area that is missing? 1.What is in the list that doesnt pertain to ontologies? 1.If you were looking for information about ontologies – from an expert point of view – would you use any of these concepts to search? Which ones are missing? What shouldnt be in the list? 1.If you were looking for information about ontologies from a novices point of view – what is missing from the list of concepts? What shouldnt be there?

5 Step by Step Approach Step 6. Test the Categorization Profile against the content –Define the xml output structure for the metadata –Run the profile against the content –Review the categorization results –Accept/refine the profile Other steps to creating the full ontology –Determining what kind of functionality you need to support use of the ontologized content –…search & discovery system –…browse of categories of content –…reporting –…recommender engines


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