Refining occurrences - Revision history

Akivela: /* Copy occurrence to topic's base name or variant name */

2013-07-20T18:24:21Z

‎Copy occurrence to topic's base name or variant name

Akivela: /* Make occurrence with topic's name */

2013-07-20T18:23:19Z

‎Make occurrence with topic's name

Akivela: /* Copy and move occurrence to different scope */

2013-07-20T18:21:38Z

‎Copy and move occurrence to different scope

Akivela: /* Replace text in occurrences */

2013-07-20T18:20:32Z

‎Replace text in occurrences

Akivela: /* Copy occurrence to topic's base name or variant name */

2013-07-20T18:13:57Z

‎Copy occurrence to topic's base name or variant name

Akivela: /* Construct topic's subject with occurrence */

2013-07-20T18:13:38Z

‎Construct topic's subject with occurrence

Akivela: /* Occurrence editor */

2012-04-27T17:26:44Z

‎Occurrence editor

Akivela: /* Conclusions */

2011-03-30T09:26:28Z

‎Conclusions

Akivela: /* Conclusions */

2011-03-30T09:24:13Z

‎Conclusions

Akivela: /* Convert occurrences to associations */

2010-12-23T21:57:59Z

‎Convert occurrences to associations

@@ Line 210: / Line 210: @@
 === Copy occurrence to topic's base name or variant name ===
-Sometimes an occurrence may contain a name for the topic. This is especially true, if you have imported RDF resources to Wandora. Wandora has a feature that copies occurrence text to topic's base name. Feature starts with menu option '''Topics > Base names > Make base name with occurrence...''' in context of a topic selection. Before Wandora can continue, Wandora user must address occurrence type and scope. User should note that the feature doesn't override existing base names i.e. if topic already has a base name, feature doesn't change it. To really set topics' base names, remove all base names first with context menu option '''Topics > Base names > Remove base names...'''. User should also note that Wandora merges topics with equal base name.
+Sometimes an occurrence may contain a name for the topic. This is especially true, if you have imported RDF resources to Wandora. Wandora has a feature that copies occurrence text to topic's base name. Feature starts with menu option '''Topics > Base names > Make base name with an occurrence...''' in context of a topic selection. Before Wandora can continue, Wandora user must address occurrence type and scope. User should note that the feature doesn't override existing base names i.e. if topic already has a base name, feature doesn't change it. To really set topics' base names, remove all base names first with context menu option '''Topics > Base names > Remove base names...'''. User should also note that Wandora merges topics with equal base name.
-To transform an occurrence to topic's variant name, use feature at context menu option '''Topics > Variant names > Make display variant with an occurrence...'''.
+To transform an occurrence to topic's variant name, use feature at context menu option '''Topics > Variant names > Make display variants with occurrences...'''.
 === Make occurrence with topic's name ===

@@ Line 216: / Line 216: @@
 === Make occurrence with topic's name ===
-Previous chapter reviewed a feature used to transform an occurrence to a topic name. Wandora features a counter operation used to make occurrences with topics' names. Selecting context menu option '''Topics > Occurrences > Make occurrence with base name...''' or context menu option '''Topics > Occurrences > Make occurrence with variant name...''' or '''Topics > Occurrences > Make occurrences with all variant names...'''.
+Previous chapter reviewed a feature used to transform an occurrence to a topic name. Wandora features a counter operation used to make occurrences with topics' names. Selecting context menu option '''Topics > Occurrences > Make occurrence with base names...''' or context menu option '''Topics > Occurrences > Make occurrence with variant names...''' or '''Topics > Occurrences > Make occurrences with all variant names...'''.
 === Construct topic's subject with occurrence ===

← Older revision		Revision as of 18:21, 20 July 2013
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	=== Copy and move occurrence to different scope ===		=== Copy and move occurrence to different scope ===

−	Scope usually represents the language of occurrence text. Sometimes Wandora user may want to copy or move occurrences to another scope. First, Wandora user should make a topic selection. Occurrence copy or move applies only to selected topics. Then, Wandora user should right clicks selected topics and choose '''Topics > Occurrences > Copy to other scope...''' or '''Topics > Occurrences > Move to other scope...'''. Both options open up a dialog window (See image below) used to specify source and target occurrences. Dialog window has also a checkbox to specify if Wandora should override existing occurrences and if Wandora should also copy occurrences that are ''null'' i.e. there is no source occurrence available.	+	Scope usually represents the language of occurrence text. Sometimes Wandora user may want to copy or move occurrences to another scope. First, Wandora user should make a topic selection. Occurrence copy or move applies only to selected topics. Then, Wandora user should right clicks selected topics and choose '''Topics > Occurrences > Copy occurrences to other scope...''' or '''Topics > Occurrences > Move occurrences to other scope...'''. Both options open up a dialog window (See image below) used to specify source and target occurrences. Dialog window has also a checkbox to specify if Wandora should override existing occurrences and if Wandora should also copy occurrences that are ''null'' i.e. there is no source occurrence available.

← Older revision		Revision as of 18:20, 20 July 2013
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	=== Replace text in occurrences ===		=== Replace text in occurrences ===

−	To replace a text in occurrences Wandora user must first select a set of topics. Replace is performed only for occurrences in selected topics. Then user should right click the topic selection, and choose context menu option '''Topics > Occurrences > ~~Regex replace~~...''' or '''Topics > Occurrences > ~~Regex replace~~ all...'''. First option asks user occurrence type and scope while the second option seeks given pattern in all occurrences. ~~Then~~ Wandora opens up '''Regular Expressions Replacer''', a specific dialog window in Wandora used to build and test regular expressions (See image below). Regular expression replacer accepts [http://download.oracle.com/javase/6/docs/api/java/util/regex/Pattern.html Java Pattern] type regular expressions. When user clicks the '''Apply''' button, Wandora loops over the topic selection and tries to match given regular expression to occurrence. If regular expression matches the occurrence (or part of it), Wandora replaces the match with given text.	+	To replace a text in occurrences Wandora user must first select a set of topics. Replace is performed only for occurrences in selected topics. Then user should right click the topic selection, and choose context menu option '''Topics > Occurrences > Modify occurrences with a regex...''' or '''Topics > Occurrences > Modify all occurrences with a regex...'''. First option asks user occurrence type and scope while the second option seeks given regular expression pattern in all occurrences. Wandora opens up '''Regular Expressions Replacer''', a specific dialog window in Wandora used to build and test regular expressions (See image below). Regular expression replacer accepts [http://download.oracle.com/javase/6/docs/api/java/util/regex/Pattern.html Java Pattern] type regular expressions. When user clicks the '''Apply''' button, Wandora loops over the topic selection and tries to match given regular expression to occurrence. If regular expression matches the occurrence (or part of it), Wandora replaces the match with given text.

@@ Line 212: / Line 212: @@
 Sometimes an occurrence may contain a name for the topic. This is especially true, if you have imported RDF resources to Wandora. Wandora has a feature that copies occurrence text to topic's base name. Feature starts with menu option '''Topics > Base names > Make base name with occurrence...''' in context of a topic selection. Before Wandora can continue, Wandora user must address occurrence type and scope. User should note that the feature doesn't override existing base names i.e. if topic already has a base name, feature doesn't change it. To really set topics' base names, remove all base names first with context menu option '''Topics > Base names > Remove base names...'''. User should also note that Wandora merges topics with equal base name.
-To transform an occurrence to topic's variant name, use feature at context menu option '''Topics > Variant names > Make display variant with occurrence...'''.
+To transform an occurrence to topic's variant name, use feature at context menu option '''Topics > Variant names > Make display variant with an occurrence...'''.
 === Make occurrence with topic's name ===

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 === Construct topic's subject with occurrence ===
-An occurrence may contain an identifier that suits well a basis of topic's subject. To construct an additional subject identifier based on an occurrence for a topic, select context menu option '''Topics > Subject identifiers > Make SI with occurrence...'''. Wandora user must specify occurrence type, occurrence scope, and a template pattern for subject identifiers.
+An occurrence may contain an identifier that suits well a basis of topic's subject. To construct an additional subject identifier based on an occurrence for a topic, select context menu option '''Topics > Subject identifiers > Make subject identifier with an occurrence...'''. Wandora user must specify occurrence type, occurrence scope, and a template pattern for subject identifiers.
-Similarly, choosing menu option '''Topics > Subject locators > Make SL with occurrence...''' creates topic a subject locator based on occurrence text.
+Similarly, choosing menu option '''Topics > Subject locators > Make subject locator with an occurrence...''' creates topic a subject locator based on occurrence text.
 == Conclusions ==
 This tutorial has documented some advanced methods used to transform textual information to graph nodes and edges in context of Wandora application and Topic Maps. Wandora features many information extractors that distill topics and associations out of occurrence text. Wandora user can process one or many occurrences at a time. Reader should notice that topic maps are able to store both unstructured text in occurrences and graph nodes and edges as topics and associations. In other words Topic Maps are capable to store both well-structured and unstructured information. This duality makes topic maps an ideal solution for data-mining applications where user has to classify large collections of text documents, for example.

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 * '''Make topics with selection and associate'''. Option creates a topic and sets selected text fragment to topic's base name. Furthermore, option gives a random subject identifier to topic. Created topic is associated with the occurrence carrier topic. Association type is '''Occurrence distilled association''' and roles '''Occurrence carrier''' and '''Occurrence distilled topic'''.
 * '''Find topics in occurrences...'''. This option is useful when you have an existing vocabulary and want to spot vocabulary terms out of given occurrence.  Option loops over all topics in Wandora and tries to find topic's base name in occurrence text. If occurrence text contains topic's base name, topic is associated with the occurrence carrier. Association type is '''Occurrence association''' and roles '''Occurrence container''' and '''Topic in occurrence'''.
-* '''Find topics with similar occurrence...''' option searches for topics containing similar occurrence text. Occurrence texts are compared using ''Levensthein distance'' with threshold value 0.75. To change the distance metric and threshold value, keep CTRL key pressed while starting the menu option. Wandora uses [http://staffwww.dcs.shef.ac.uk/people/S.Chapman/simmetrics.html Simmetrics library] to measure string similarity. Available metrics are [http://staffwww.dcs.shef.ac.uk/people/S.Chapman/simmetrics/uk/ac/shef/wit/simmetrics/similaritymetrics/package-summary.html here].
+* '''Find topics with similar occurrence...''' option searches for topics containing similar occurrence text. Occurrence texts are compared using ''Levensthein distance'' with threshold value 0.75. To change the distance metric and threshold value, keep CTRL key pressed while starting the menu option. Wandora uses [http://sourceforge.net/projects/simmetrics/ Simmetrics library] to measure string similarity.
 * '''Classify with OpenCalais''' option sends the occurrence text or selected occurrence text fragment to OpenCalais web service for classification. Service returns keywords which are transformed to topics and associated to occurrence carrier topic. [[OpenCalais classifier]] is also a general extractor in Wandora.
 * '''Classify with SemanticHacker''' option sends occurrence text to SemanticHacker web service. Service returns a set of weighted terms and Wandora transforms these to topics, and associates topics to the occurrence carrier. [[SemanticHacker classifier]] is also a general extractor in Wandora. Personal API key is required for SemanticHacker classification.

← Older revision		Revision as of 09:26, 30 March 2011
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	== Conclusions ==		== Conclusions ==

−	This tutorial has documented some advanced methods used to transform textual information to graph nodes and edges in context of Wandora application and Topic Maps. Wandora features many information extractors that distill topics and associations out of occurrence text. Wandora user can process one or many occurrences at a time~~. Batch processing multiple occurrence during a single run is very useful if user has a large document collection~~. Reader should notice that topic maps are able to store both unstructured text in occurrences and graph nodes and edges as topics and associations. In other words Topic Maps are capable to store both well-structured and unstructured information. This duality makes topic maps an ideal solution for data-mining applications where user has to classify large collections of text documents, for example.	+	This tutorial has documented some advanced methods used to transform textual information to graph nodes and edges in context of Wandora application and Topic Maps. Wandora features many information extractors that distill topics and associations out of occurrence text. Wandora user can process one or many occurrences at a time. Reader should notice that topic maps are able to store both unstructured text in occurrences and graph nodes and edges as topics and associations. In other words Topic Maps are capable to store both well-structured and unstructured information. This duality makes topic maps an ideal solution for data-mining applications where user has to classify large collections of text documents, for example.

← Older revision		Revision as of 09:24, 30 March 2011
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	== Conclusions ==		== Conclusions ==

−	This tutorial has documented some advanced methods used to transform textual information to graph nodes and edges in context of Wandora application and Topic Maps. Reader should notice that topic maps are able to store both unstructured text in occurrences and graph nodes and edges as topics and associations. In other words Topic Maps are capable to store both well-structured and unstructured information. This duality makes topic maps an ideal solution for data-mining applications where user has to classify large collections of text documents, for example.	+	This tutorial has documented some advanced methods used to transform textual information to graph nodes and edges in context of Wandora application and Topic Maps. Wandora features many information extractors that distill topics and associations out of occurrence text. Wandora user can process one or many occurrences at a time. Batch processing multiple occurrence during a single run is very useful if user has a large document collection. Reader should notice that topic maps are able to store both unstructured text in occurrences and graph nodes and edges as topics and associations. In other words Topic Maps are capable to store both well-structured and unstructured information. This duality makes topic maps an ideal solution for data-mining applications where user has to classify large collections of text documents, for example.

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 === Convert occurrences to associations ===
-Sometimes information stored to an occurrence could be a topic itself. For example, a topic representing an instance of a person may contain an occurrence representing parson's birth year. It is a matter of ontology designer's choice to model birth years as occurrences. Some other ontology might model years as topics and birth years as associations between person and year topics. Thus, it is somehow a natural operation to convert occurrences to topics, and then associate created topics with occurrence carrier topics. Wandora features such an operation. First Wandora user must address topics in which she wants to convert occurrences to associations. Right clicking the topic selection and choosing context menu option '''Topics > Associations > Make associations with occurrences...''' starts the operation. Before Wandora performs transition, user should select occurrence type, occurrence scope, association role topic, and give subject identifier pattern.
+Sometimes information stored to an occurrence could be a topic itself. For example, a topic representing an instance of a person may contain an occurrence representing person's birth year. It is a matter of ontology designer's choice to model birth years as occurrences. Some other ontology might model years as topics and birth years as associations between person and year topics. Thus, it is somehow a natural operation to convert occurrences to topics, and then associate created topics with occurrence carrier topics. Wandora features such an operation. First Wandora user must address topics in which she wants to convert occurrences to associations. Right clicking the topic selection and choosing context menu option '''Topics > Associations > Make associations with occurrences...''' starts the operation. Before Wandora performs transition, user should select occurrence type, occurrence scope, association role topic, and give subject identifier pattern.
 === Copy occurrence to topic's base name or variant name ===