Abstract: Client side code of a web application can be received by a mobile device. The mobile device can automatically inject mobile aware code into the client side code of the web application. The mobile aware code can modify the client side code of the web application for use by the mobile device, wherein the client side code of the web application is not modified for use by the mobile device prior to the mobile aware code being injected. The client side code of the web application modified by the mobile aware code can be executed by the mobile device.

Abstract: Client side code of a web application can be received by a mobile device. The mobile device can automatically inject mobile aware code into the client side code of the web application. The mobile aware code can modify the client side code of the web application for use by the mobile device, wherein the client side code of the web application is not modified for use by the mobile device prior to the mobile aware code being injected. The client side code of the web application modified by the mobile aware code can be executed by the mobile device.

Abstract: A computer-implemented method, system and computer program product for maintaining a target accuracy level. A target accuracy level is received. Thresholds including ongoing adjustable automation thresholds for categories are computed based on the target accuracy level. Data is received and a classification score for the categories is generated with respect to the data based on a category knowledgebase. Furthermore, a classification score is detected for a category with a higher classification score than other categories of the plurality of categories that exceeds an ongoing adjustable automation threshold. A reply to the data is automatically sent out based on the category with the higher classification score. The action, the suggestion list, and corresponding received feedback are monitored to generate a historical performance dataset. An actual accuracy level is then determined based on the historical performance dataset.

Abstract: Techniques for processing a speech to text query are described herein. The techniques may include receiving a plurality of speech to text translation alternatives for a phrase of a natural language query, and tagging and parsing each of the translation alternatives based on a static analysis of the known domain that is at least partially structured, known tags of the known domain, and custom rules. The techniques may also include ranking the translation alternatives based on the tagging and parsing and translating the phrase based on the ranking.

Abstract: Techniques for processing a speech to text query are described herein. The techniques may include receiving a plurality of speech to text translation alternatives for a phrase of a natural language query, and tagging and parsing each of the translation alternatives based on a static analysis of the known domain that is at least partially structured, known tags of the known domain, and custom rules. The techniques may also include ranking the translation alternatives based on the tagging and parsing and translating the phrase based on the ranking.

Abstract: A computer-implemented method, system and computer program product for maintaining a target accuracy level. A target accuracy level is received. Thresholds including ongoing adjustable automation thresholds for categories are computed based on the target accuracy level. Data is received and a classification score for the categories is generated with respect to the data based on a category knowledgebase. Furthermore, a classification score is detected for a category with a higher classification score than other categories of the plurality of categories that exceeds an ongoing adjustable automation threshold. A reply to the data is automatically sent out based on the category with the higher classification score. The action, the suggestion list, and corresponding received feedback are monitored to generate a historical performance dataset. An actual accuracy level is then determined based on the historical performance dataset.

Abstract: Techniques for analyzing a repository are described herein. A method for analyzing a repository may include obtaining a list of known persons in a repository based on objects, users, and groups retrieved from the repository. The method may further select one of the objects having a field and a value, and then determine whether the field of the selected object is a facet based on a probability that the field of the selected object has a limited number of possible values. In analyzing the repository, a repository information archive may be generated. The repository information archive may include the relationship between the selected object and at least one other object, statistics and counts related to properties in the selected objects, and whether or not the field of the selected object is a facet.

Abstract: Techniques for analyzing a repository are described herein. A method for analyzing a repository may include obtaining a list of known persons in a repository based on objects, users, and groups retrieved from the repository. The method may further select one of the objects having a field and a value, and then determine whether the field of the selected object is a facet based on a probability that the field of the selected object has a limited number of possible values. In analyzing the repository, a repository information archive may be generated. The repository information archive may include the relationship between the selected object and at least one other object, statistics and counts related to properties in the selected objects, and whether or not the field of the selected object is a facet.

Abstract: Techniques for generating query language statements for a document repository are described herein. An example method includes detecting a search query corresponding to a document repository and generating a modified search query by adding atomic tags to the search query, the atomic tags being based on prior knowledge obtained by static analysis of the document repository and semantic rules. The method also includes generating enriched tags based on combinations of the atomic tags and any previously identified enriched tags and generating a first set of conditions based on combinations of the atomic tags and the generated enriched tags and generating a second set of conditions based on free-text conditions. The method also includes generating the query language statements based on the first set of conditions and the second set of conditions and displaying a plurality of documents from the document repository that satisfy the query language statements.

Abstract: Techniques for generating query language statements for a document repository are described herein. An example method includes detecting a search query corresponding to a document repository and generating a modified search query by adding atomic tags to the search query, the atomic tags being based on prior knowledge obtained by static analysis of the document repository and semantic rules. The method also includes generating enriched tags based on combinations of the atomic tags and any previously identified enriched tags and generating a first set of conditions based on combinations of the atomic tags and the generated enriched tags and generating a second set of conditions based on free-text conditions. The method also includes generating the query language statements based on the first set of conditions and the second set of conditions and displaying a plurality of documents from the document repository that satisfy the query language statements.

Abstract: An approach to creating a canonical representation of a JavaScript API. Objects associated with the JavaScript API are instantiated, creating entry points for analysis. A list of discovered objects is created based on parsing a document object model associated with the JavaScript API. The objects are instrumented and statically analyzed, creating an infrastructure associated with the JavaScript API. The infrastructure is updated based on analyzing the objects while the interface is being used and the objects are executing. A canonical representation, based on the updated infrastructure, is generated for further operations.

Abstract: An approach to creating a canonical representation of a JavaScript API. Objects associated with the JavaScript API are instantiated, creating entry points for analysis. A list of discovered objects is created based on parsing a document object model associated with the JavaScript API. The objects are instrumented and statically analyzed, creating an infrastructure associated with the JavaScript API. The infrastructure is updated based on analyzing the objects while the interface is being used and the objects are executing. A canonical representation, based on the updated infrastructure, is generated for further operations.

Abstract: An approach to creating a canonical representation of a JavaScript API. Objects associated with the JavaScript API are instantiated, creating entry points for analysis. A list of discovered objects is created based on parsing a document object model associated with the JavaScript API. The objects are instrumented and statically analyzed, creating an infrastructure associated with the JavaScript API. The infrastructure is updated based on analyzing the objects while the interface is being used and the objects are executing. A canonical representation, based on the updated infrastructure, is generated for further operations.

Abstract: Techniques for generating query language statements for a document repository are described herein. An example method includes detecting a search query corresponding to a document repository and generating a modified search query by adding atomic tags to the search query, the atomic tags being based on prior knowledge obtained by static analysis of the document repository and semantic rules. The method also includes generating enriched tags based on combinations of the atomic tags and any previously identified enriched tags and generating a first set of conditions based on combinations of the atomic tags and the generated enriched tags and generating a second set of conditions based on free-text conditions. The method also includes generating the query language statements based on the first set of conditions and the second set of conditions and displaying a plurality of documents from the document repository that satisfy the query language statements.

Abstract: Techniques for processing a speech to text query are described herein. The techniques may include receiving a plurality of speech to text translation alternatives for a phrase of a natural language query, and tagging and parsing each of the translation alternatives based on a static analysis of the known domain that is at least partially structured, known tags of the known domain, and custom rules. The techniques may also include ranking the translation alternatives based on the tagging and parsing and translating the phrase based on the ranking.

Abstract: Techniques for processing a speech to text query are described herein. The techniques may include receiving a plurality of speech to text translation alternatives for a phrase of a natural language query, and tagging and parsing each of the translation alternatives based on a static analysis of the known domain that is at least partially structured, known tags of the known domain, and custom rules. The techniques may also include ranking the translation alternatives based on the tagging and parsing and translating the phrase based on the ranking.

Abstract: Techniques for generating query language statements for a document repository are described herein. An example method includes detecting a search query corresponding to a document repository and generating a modified search query by adding atomic tags to the search query, the atomic tags being based on prior knowledge obtained by static analysis of the document repository and semantic rules. The method also includes generating enriched tags based on combinations of the atomic tags and any previously identified enriched tags and generating a first set of conditions based on combinations of the atomic tags and the generated enriched tags and generating a second set of conditions based on free-text conditions. The method also includes generating the query language statements based on the first set of conditions and the second set of conditions and displaying a plurality of documents from the document repository that satisfy the query language statements.

Abstract: Techniques for analyzing a repository are described herein. A method for analyzing a repository may include obtaining a list of known persons in a repository based on objects, users, and groups retrieved from the repository. The method may further select one of the objects having a field and a value, and then determine whether the field of the selected object is a facet based on a probability that the field of the selected object has a limited number of possible values. In analyzing the repository, a repository information archive may be generated. The repository information archive may include the relationship between the selected object and at least one other object, statistics and counts related to properties in the selected objects, and whether or not the field of the selected object is a facet.

Abstract: Techniques for analyzing a repository are described herein. A method for analyzing a repository may include obtaining a list of known persons in a repository based on objects, users, and groups retrieved from the repository. The method may further select one of the objects having a field and a value, and then determine whether the field of the selected object is a facet based on a probability that the field of the selected object has a limited number of possible values. In analyzing the repository, a repository information archive may be generated. The repository information archive may include the relationship between the selected object and at least one other object, statistics and counts related to properties in the selected objects, and whether or not the field of the selected object is a facet.

Abstract: An approach to creating a canonical representation of a JavaScript API. Objects associated with the JavaScript API are instantiated, creating entry points for analysis. A list of discovered objects is created based on parsing a document object model associated with the JavaScript API. The objects are instrumented and statically analyzed, creating an infrastructure associated with the JavaScript API. The infrastructure is updated based on analyzing the objects while the interface is being used and the objects are executing. A canonical representation, based on the updated infrastructure, is generated for further operations.