Data is organized in a hierarchical data tree having nodes, and is formatted in human-readable data according to a schema. The data is canonically ordered in correspondence with a canonical ordering of a schema dictionary generated from the schema. The canonically ordered data is encoded into binary, including for each node, removing a label of the node, and adding a sequence number of the node corresponding to the canonical ordering, in binary.

Systems and methods receive an asset identification and one or more criterion to at least one of a locale, a market, a target, or an experiment and process a graph having a plurality of sub-graphs to define an asset having one or more desired variants. The asset is then published having the one or more desired variants. Multiple entities are represented as a single entity, which can be used for localization of the asset (e.g., image, video, custom data) or pages. By associating one entity (e.g., an image) across all variations of the entity, the needed storage space for the plurality of assets (e.g., images or videos) is reduced.

Aspects of the present invention disclose a method for automatic delineation and extraction of tabular data in portable document format (PDF). The method includes one or more processors extracting metadata corresponding to tabular data in a text-based portable document format (PDF), wherein the metadata is associated with characters and border lines of the tabular data. The method further includes generating a graph structure corresponding to the tabular data in the text-based PDF based at least in part on the metadata. The method further includes generating a vector representation of the graph structure. The method further includes constructing a tree structure corresponding to the tabular data based at least in part on the vector representation.

Aspects of the present invention disclose a method for automatic delineation and extraction of tabular data in portable document format (PDF). The method includes one or more processors extracting metadata corresponding to tabular data in a text-based portable document format (PDF), wherein the metadata is associated with characters and border lines of the tabular data. The method further includes generating a graph structure corresponding to the tabular data in the text-based PDF based at least in part on the metadata. The method further includes generating a vector representation of the graph structure. The method further includes constructing a tree structure corresponding to the tabular data based at least in part on the vector representation.

An information analyzing apparatus 10 includes: a detection unit 11 configured to detect unknown word information expressing an unknown word contained in document information collected from web content; and a conversion unit 12 configured to, using forum expression information contained in the unknown word information detected, converting the forum expression information into formal expression information by referring to expression conversion information for converting a forum expression into a formal expression set in advance.

An information analyzing apparatus 10 includes: a detection unit 11 configured to detect unknown word information expressing an unknown word contained in document information collected from web content; and a conversion unit 12 configured to, using forum expression information contained in the unknown word information detected, converting the forum expression information into formal expression information by referring to expression conversion information for converting a forum expression into a formal expression set in advance.

The invention relates to a method, the method comprising: recording user input through a virtual keyboard of a device for generating a user input history; determining, based on the user input history, at least one character associated with at least one correction operation in a context of the user input through the virtual keyboard of the device; generating a control signal for adjusting an output of the at least one character on the virtual keyboard, the at least one character is selected based on the at least one correction operation. The invention also relates to a computer program and to an apparatus.

The invention relates to a method, the method comprising: recording user input through a virtual keyboard of a device for generating a user input history; determining, based on the user input history, at least one character associated with at least one correction operation in a context of the user input through the virtual keyboard of the device; generating a control signal for adjusting an output of the at least one character on the virtual keyboard, the at least one character is selected based on the at least one correction operation. The invention also relates to a computer program and to an apparatus.

Disclosed herein are system, method, and computer program product embodiments for processing a written-language contract using an industry-specific natural language processing model to determine flows or actions to undertake in a Customer Relationship Management (CRM) solution. A CRM solution may include the ability to receive or create a binding natural-language contract. The CPQ or CRM system may use natural language processing (NLP) to determine terms and conditions included in a natural-language contract. The NLP may further use an industry-specific model that may be determined based on information in the CRM solution to more efficiently and accurately analyze the natural-language contract. The CRM solution may further receive a legal language construct and convert the terms of the legal language construct into a smart contract.

Disclosed herein are system, method, and computer program product embodiments for processing a written-language contract using an industry-specific natural language processing model to determine flows or actions to undertake in a Customer Relationship Management (CRM) solution. A CRM solution may include the ability to receive or create a binding natural-language contract. The CPQ or CRM system may use natural language processing (NLP) to determine terms and conditions included in a natural-language contract. The NLP may further use an industry-specific model that may be determined based on information in the CRM solution to more efficiently and accurately analyze the natural-language contract. The CRM solution may further receive a legal language construct and convert the terms of the legal language construct into a smart contract.