In some aspects described herein, a computer-based system that is capable of constructing digital documents is provided. In some implementations, a machine learning system is provided that learns certain terms within a document. The terms may be, for example, part of a document that forms a legally-binding contract between two entities. In one implementation of the machine learning system, the machine learning system interoperates within a user interface to show predictions of certain terms within the document to the user. Further, the machine learning system may capture user answers relating to certain terms and provide feedback into the system that learns during operation of the system, improving user interactions, accuracy and reducing the number of user interactions.

In some aspects described herein, a computer-based system that is capable of constructing digital documents is provided. In some implementations, a machine learning system is provided that learns certain terms within a document. The terms may be, for example, part of a document that forms a legally-binding contract between two entities. In one implementation of the machine learning system, the machine learning system interoperates within a user interface to show predictions of certain terms within the document to the user. Further, the machine learning system may capture user answers relating to certain terms and provide feedback into the system that learns during operation of the system, improving user interactions, accuracy and reducing the number of user interactions.

Technologies and techniques for supporting an autonomous vehicle wherein objects in surroundings of the vehicle are captured by a sensor system, and wherein objects are identified and recognized by object recognition from captured data relating to the surroundings. When an unknown object is present in the surroundings, the unknown object if found in at least one database, typical properties of the unknown object are determined on the basis of the search result, a recommended course of action is derived for the autonomous vehicle on the basis of the typical properties of the unknown object, and the derived recommended course of action are provided to the vehicle.

Technologies and techniques for supporting an autonomous vehicle wherein objects in surroundings of the vehicle are captured by a sensor system, and wherein objects are identified and recognized by object recognition from captured data relating to the surroundings. When an unknown object is present in the surroundings, the unknown object if found in at least one database, typical properties of the unknown object are determined on the basis of the search result, a recommended course of action is derived for the autonomous vehicle on the basis of the typical properties of the unknown object, and the derived recommended course of action are provided to the vehicle.

A method of embodying an online media service having a multiple voice system includes a first operation of collecting preset online articles and content from a specific media site and displaying the online articles and content on a screen of a personal terminal, a second operation of inputting a voice of a subscriber or setting a voice of a specific person among voices that are pre-stored in a database, a third operation of recognizing and classifying the online articles and content, a fourth operation of converting the classified online articles and content into speech, and a fifth operation of outputting the online articles and content using the voice of the subscriber or the specific person, which is set in the second operation.

An information processing apparatus includes a processor configured to acquire a text recognition result including a text string included in an image and position information of the text string in the image, display the text string included in the text recognition result, and specify, in a case where the displayed text string is corrected, position information corresponding to the corrected text string, among pieces of the position information associated with each text string included in the text recognition result.

A data storage system includes storage and a global enumerator. The storage stores data chunks, object level metadata associated with portions of the data chunks, and chunk level metadata associated with respective data chunks. The global enumerator obtains an update request including a metadata characteristic and update data; in response to obtaining the update request: matches the metadata characteristic to at least one selected from a group consisting of a portion of the object level metadata and a portion of the chunk level metadata to identify an implicated metadata portion; and modifies, based on the update data, the implicated metadata portion.

A data storage system includes storage and a global enumerator. The storage stores data chunks, object level metadata associated with portions of the data chunks, and chunk level metadata associated with respective data chunks. The global enumerator obtains an update request including a metadata characteristic and update data; in response to obtaining the update request: matches the metadata characteristic to at least one selected from a group consisting of a portion of the object level metadata and a portion of the chunk level metadata to identify an implicated metadata portion; and modifies, based on the update data, the implicated metadata portion.

Computer-readable media, methods, and systems are disclosed for storing and analyzing dynamic data within a semantic data store. The dynamic data comprises one or more types of data having a normalized data schema. A dynamic data manager interfaces with the semantic data store to instruct storage of the data. The data may be received through an event service from either of an external data source or an internal data source.

Systems and methods for generating asynchronous application programming interface (API) documents are generally described. In various examples, a topic discovery request may be sent to a message broker. A list of topics may be received from the message broker. First identifier data identifying a first topic of the list of topics may be received from the message broker. A first message may be received from the message broker, where the first message pertains to the first topic. First schema may be determined using the first message. The first schema data may describe content of the first message and organization of the content of the first message. The first identifier data may be stored in a first data structure in association with the first schema data.