A technique allows a credential manager application on a client computer system to identify fields and forms on a web page. An analysis server may automatically crawl web pages and identify the fields and form, then push the information to the client computer system for use by the credential manager. If the credential manager discovers the information is not available, the credential manager may analyze the web form to discover the fields and form information, then provide the discovered information to the analysis server for providing to other client computers. The analysis server may use crowd-sourcing for asynchronous verification of field and form information discovered by the analysis server or provided by the client computer.

A computing device for expert case-based natural language learning includes a blackboard database, a top level mapper, and a bottom level case-based inference engine, and a bottom level translator. The blackboard database is configured to store context information corresponding to case semantics associated with natural language sentential forms. The case semantics include situation semantics and action semantics. The top level mapper is configured to query the blackboard database for the context information, map the situation semantics to the action semantics using the context information to form new case semantics, and store the new case semantics in a bottom level case database. The bottom level case-based inference engine is configured to match an input natural language sentential form to a matching case semantic stored in the bottom level case database. The bottom level translator is configured to translate the matching case semantic into natural language sentential form.

This disclosure relates generally to quality evaluation of collaborative text input, and more particularly to system and method for quality evaluation of collaborative text inputs using Long Short Term Memory (LSTM) networks. In one embodiment, the method includes receiving an input data associated with a task to be accomplished collaboratively and sequentially by a plurality of contributors. The input data includes task-wise data sequence of contributor's post-edit submissions. A plurality of features are extracted from the input data. Based on the plurality of features, a plurality of input sequences are constructed. The input sequences include a plurality of concatenated feature vectors, where each of the concatenated feature vectors includes a post-edit feature vector and a contributor representation feature vector. The input sequences are modelled as a LSTM network, where the LSTM network is utilized to train a binary classifier for quality evaluation of the post-edit submission.

A method and system is provided for facilitating affiliate link generation using a web browser application. A publisher enables the system by identifying a webpage on an affiliate web site. The system performs an initial assessment of the page to extract webpage information, which is compared to information stored in a database. If the extracted information matches stored information, a record of the webpage is displayed and an affiliate link is dynamically generated for immediate use. If the extracted information does not match stored information, a new record of the webpage is created. If the webpage contains product-specific data, a product-specific record is stored. If the webpage does not contain product-specific data, a non-product record is stored. An affiliate link is then dynamically created. The new record of the product and dynamically created affiliate link is added to the database for immediate use.

A method, system and voice browser execute voice applications to perform a voice-based function. A document is retrieved and parsed to create a parse tree. Script code is created from the parse tree, thereby consuming part of the parse tree to create a reduced parse tree. The reduced parse tree is stored in a cache for subsequent execution to perform the voice-based function.

Embodiments of the invention relate to systems and methods for creating a form for receiving data relating to a health care incident. A dictionary of field objects is provided in a metabase, where a field object defines attributes, and an instance of a field object is a form field. A request to create a user-defined field object is received and it is determined that the user-defined field object is not in the dictionary of field objects in the metabase. The user-defined field object is generated by defining attributes for the user-defined field object, where at least one attribute is a presentation attribute for a form field within a form. The user-defined field object is added to the dictionary of field objects in the metabase and the user-defined field object is linked to a data location in a persistent store. The form is generated, where the form is an ordered collection of form fields, where at least one form field is an instance of the user-defined field object and is displayed according to the at least one presentation attribute.

A method includes associating, for each one of a plurality of answer definitions, at least one or more pattern-form questions, wherein each answer definition has an associated jump target that defines a respective entry point into the workspace analytics system to provide information responsive to the associated one or more pattern-form questions. The method further includes receiving a user input including capturing input text defining a natural language user query, matching the received input text to one of the pattern-form questions thereby selecting the jump target associated with the matched pattern-form question, and generating a response to the natural language user query by retrieving information from the workspace analytics system by referencing a link based on the selected jump target and zero or more parameters values.

Large and complex data sets can be difficult to view on devices with small screens, such as on smartphones, or in small windows on devices with large screens. The presently disclosed systems, methods and apparatus can determine characteristics associated with a display used to display a requested resource. Based on these determined characteristics, the systems and methods can determine whether the requested resource should be reformatted to fit the display. The requested resource can be reformatted to allow a user to consume complex data on a small display easily and effectively. In some embodiments, this can be done by ensuring that the current data context, previously provided by row/column headers, are always in view in a compact format.

An analytical computing environment for large data sets comprises a software platform for data management. The platform provides various automation and self-service features to enable those users to rapidly provision and manage an agile analytics environment. The platform leverages a metadata repository, which tracks and manages all aspects of the data lifecycle. The repository maintains various types of platform metadata including, for example, status information (load dates, quality exceptions, access rights, etc.), definitions (business meaning, technical formats, etc.), lineage (data sources and processes creating a data set, etc.), and user data (user rights, access history, user comments, etc.). Within the platform, the metadata is integrated with all platform services, such as load processing, quality controls and system use. As the system is used, the metadata gets richer and more valuable, supporting additional automation and quality controls.

The disclosure relates to transferred learning from a first language (e.g., a source language for which a semantic parser has been defined) to a second language (e.g., a target language for which a semantic parser has not been defined). A system may use knowledge from a trained model in one language to model another language. For example, the system may transfer knowledge of a semantic parser from a first (e.g., source) language to a second (e.g., target) language. Such transfer of knowledge may occur and be useful when the first language has sufficient training data but the second language has insufficient training data. The foregoing transfer of knowledge may extend the semantic parser for multiple languages (e.g., the first language and the second language).