Mechanisms are provided for performing artificial intelligence-based video question answering. A video parser parses an input video data sequence to generate situation data structure(s), each situation data structure comprising data elements corresponding to entities, and first relationships between entities, identified by the video parser as present in images of the input video data sequence. First machine learning computer model(s) operate on the situation data structure(s) to predict second relationship(s) between the situation data structure(s). Second machine learning computer model(s) execute on a received input question to predict an executable program to execute to answer the received question. The program is executed on the situation data structure(s) and predicted second relationship(s). An answer to the question is output based on results of executing the program.

Disclosed is a system and method for validating and correcting sync errors of captions of a media asset comprising a caption file, wherein each caption has a start time and an end time. The system decodes the caption file using caption decoder for generating a format agnostic XML file, a transcriber engine extracts an audio track and transcribes the audio for generating a transcript, a caption analyser identifies matching set of words in the transcript and assign a match score and classifies the captions as one of MATCHING and UNDETECTED based on the match score. The caption analyser determines sync offset for each caption that is classified as MATCHNING and the system uses a prediction engine for predicting sync offset of the captions that are classified as UNDETECTED.

Disclosed is a system and method for validating and correcting sync errors of captions of a media asset comprising a caption file, wherein each caption has a start time and an end time. The system decodes the caption file using caption decoder for generating a format agnostic XML file, a transcriber engine extracts an audio track and transcribes the audio for generating a transcript, a caption analyser identifies matching set of words in the transcript and assign a match score and classifies the captions as one of MATCHING and UNDETECTED based on the match score. The caption analyser determines sync offset for each caption that is classified as MATCHNING and the system uses a prediction engine for predicting sync offset of the captions that are classified as UNDETECTED.

In one embodiment, a system includes a wafer handling system, processing components, a controller, a virtual assistant, a natural language processing (NLP) engine, and a data-analytics engine. The wafer handling system is configured to hold one or more wafers for processing. The processing components is configured to physically treat the one or more wafers. The controller is configured to operate the processing components. The virtual assistant, in communication with the NLP engine, is configured to receive a user query from a user, understand an intent or context of the user query, and provide a context-specific response to the user query. The data-analytics engine is configured to generate and provide analytical data relating to the user query based on data collected from a plurality of data sources via one or more communication protocols.

In one embodiment, a system includes a wafer handling system, processing components, a controller, a virtual assistant, a natural language processing (NLP) engine, and a data-analytics engine. The wafer handling system is configured to hold one or more wafers for processing. The processing components is configured to physically treat the one or more wafers. The controller is configured to operate the processing components. The virtual assistant, in communication with the NLP engine, is configured to receive a user query from a user, understand an intent or context of the user query, and provide a context-specific response to the user query. The data-analytics engine is configured to generate and provide analytical data relating to the user query based on data collected from a plurality of data sources via one or more communication protocols.

A method for generating and displaying an icon associated with a topic in place of filtered content, the icon associated with functionality allowing for displaying of the filtered content, includes applying, by a filtering engine, a topic-based filter to at least a portion of a data stream. The filtering engine directs a first modification to a user interface displaying the at least the portion of the data stream, the modification comprising redacting the at least the portion of the data stream and displaying at least one icon in place of the at least the portion of the data stream, the at least one icon associated with a topic of the at least the portion of the data stream. The filtering engine receives user input via the at least one icon and directs the displaying of the at least the portion of the data stream.

A method for generating and displaying an icon associated with a topic in place of filtered content, the icon associated with functionality allowing for displaying of the filtered content, includes applying, by a filtering engine, a topic-based filter to at least a portion of a data stream. The filtering engine directs a first modification to a user interface displaying the at least the portion of the data stream, the modification comprising redacting the at least the portion of the data stream and displaying at least one icon in place of the at least the portion of the data stream, the at least one icon associated with a topic of the at least the portion of the data stream. The filtering engine receives user input via the at least one icon and directs the displaying of the at least the portion of the data stream.

Methods and systems are disclosed herein for updating a knowledge graph based on a user confirmation. A media guidance application receives a user communication and isolates a term of the user communication. The media guidance application identifies a candidate component of a knowledge graph associated with the term. The media guidance application requests user input directed to confirming whether the term is associated with the candidate component. In response to receiving the user input, the media guidance application modifies a strength of association between the term and the component.

Methods and systems are disclosed herein for updating a knowledge graph based on a user confirmation. A media guidance application receives a user communication and isolates a term of the user communication. The media guidance application identifies a candidate component of a knowledge graph associated with the term. The media guidance application requests user input directed to confirming whether the term is associated with the candidate component. In response to receiving the user input, the media guidance application modifies a strength of association between the term and the component.

This disclosure relates to extraction of tasks from documents based on a weakly supervised classification technique, wherein extraction of tasks is identification of mentions of tasks in a document. There are several prior arts addressing the problem of extraction of events, however due to crucial distinctions between events-tasks, task extraction stands as a separate problem. The disclosure explicitly defines specific characteristics of tasks, creates labelled data at a word-level based on a plurality of linguistic rules to train a word-level weakly supervised model for task extraction. The labelled data is created based on the plurality of linguistic rules for a non-negation aspect, a volitionality aspect, an expertise aspect and a plurality of generic aspects. Further the disclosure also includes a phrase expansion technique to capture the complete meaning expressed by the task instead of merely mentioning the task that may not capture the entire meaning of the sentence.