Abstract: A method, computer system, and a computer program product for coordinating supervision of at least one document processing pipeline is provided. The present invention may include receiving one or more documents. The present invention may then include parsing the received one or more documents to identify one or more performance indicators associated with the received one or more documents. The present invention may also include processing the parsed one or more documents based on a series of processor nodes. The present invention may further include identifying one or more deviations associated with the identified one or more performance indicators. The present invention may also include transferring the identified one or more deviations to a supervisor component. The present invention may then include generating at least one deviation escalation. The present invention may then further include reprocessing the generated at least one deviation escalation after a human response.

Abstract: Procedural optimization is facilitated by receiving user input for creating or modifying a body of text comprising a procedure, detecting one or more procedural steps associated with the procedure using a procedural step detection module, automatically searching within a corpus of references for one or more related procedural steps using a related procedural step extraction module, automatically identifying one or more outcomes within the corpus of references associated with the one or more related procedural steps using an outcome extraction module, automatically determining whether the one or more outcomes comprise detrimental results using an outcome analysis module, and, in response to determining a set of detrimental outcomes from the one or more outcomes that comprise detrimental results, presenting a detriment indicator within the user interface in association with the one or more procedural steps.

Abstract: The present system and method for analysing sentiment is a response to the growing availability of informal, opinionated texts like blog posts and product review websites, a field of Sentiment Analysis has sprung up in the past decade to address the interrogation about how people feel about certain topics. Sentiment Analysis expands the traditional fact-based text analysis to enable opinion-oriented information systems. The present system and method for analysing sentiment presents a novel learning system and method for classifying text as positive, negative, or objective. It is mainly based on fuzzy set theory and clustering.

Abstract: Examples herein involve detection of entities in unstructured data. Terms are extracted from unstructured data. Entities scores for the terms are calculated using information from a name probability source, a known entity database, and historical context information. The entity scores indicate a probability that the respective terms refer to entities. The presence of detected entities are indicated based on the entity scores.

Abstract: Text is intelligently annotated by first creating a topic map summarizing topics of interest of the user. A data structure is created. The topic map is used to create two linked user dictionaries, a topic dictionary reflecting topic names and a traversal dictionary reflecting the knowledge structure of a topic. Actions may be linked with topic types. When the text to be annotated is being read, the topic data structure of the topics found in the text are automatically instantiated using the dictionaries and any actions previously linked to topic types. Instantiated topic data structures are automatically attached to the text being annotated. A user GUI may be created to allow the user to access and interact with the text annotations.

Abstract: A method includes: initializing a list of token embeddings, each of the token embeddings corresponding to a tokenized word from text in a corpus of text; generating a graph for a group of consecutive words s from the text, said graph including binary relations between pairs of tokenized words of the group of consecutive words; selecting the token embeddings representing the words of the group of consecutive words from the list of token embeddings; computing a tensor of binary relations as the product between a matrix of the selected token embeddings and a tensor representing discourse relations, the computed tensor representing the binary relations between the pairs of tokenized words; computing a loss using the computed tensor; optimizing the list of token embeddings using the computed loss. The above may be repeated until the computed loss is within a predetermined range.

Abstract: Embodiments include methods, systems and computer program products for performing named entity recognition. Aspects include obtaining a text having a plurality of words and comparing each of the plurality of words to a dictionary. Aspects also include creating, based on the comparison, an annotation for at least one of the plurality of words that the least one of the plurality of words refers to a named entity. Aspects further include parsing the text to identify a part of speech for each of the plurality of words and removing the annotations from each of the at least one of the plurality of words that has a part of speech that is not one or a noun and a noun supporting adjective.

Abstract: A technique manages collaborative web sessions (CWS). The technique receives graphical content of a CWS. The technique translates a set of portions of the graphical content into text output. The technique provides the text output to a set of text application services. The set of text application services associate the text output with the CWS.

Abstract: The embodiments herein disclose methods and systems for passive wakeup of a user interaction device and configuring a dynamic wakeup time for a user interaction device, a method includes detecting an occurrence of at least one first non-voice event associated with at least one device present in an Internet of Things (IoT) environment. The method includes detecting an occurrence of at least one successive event associated with the at least one device. The method includes estimating a contextual probability of initiating at least one interaction by a user with the user interaction device on detecting the occurrence of at least one of the at least one first event and the at least one successive event. On determining the estimated contextual probability is above a pre-defined threshold value, the method includes configuring the dynamic wakeup time to switch the user interaction device to a passive wakeup state.

Abstract: The described technology is generally directed towards coordinating the generation, validation and enabling of content selection graphs in an in-memory content selection graph data store. When a set of content selection graphs is requested, a coordinator starts the generation of the relevant graphs. Upon successful generation, the coordinator starts a validation of the generated graphs against rules for the nodes/response data in the graphs. If the generated graphs pass validation, the coordinator enables the graph set for use in an in-memory cache, whereby when a request to return content selection data is received, an active graph that corresponds to the request and the current time is accessed to obtain and return the response data as the requested content selection data.

Abstract: A computer-implemented method identifies one or more concepts from a document, wherein the document comprises information on completing a task. The method computes a relevance value of an utterance with respect to completing the task using the one or more identified concepts. The method removes the utterance from a dialog model to be used for completing the task when the relevance value of the utterance is below a given threshold value.

Abstract: A system includes a communication interface, at least one processor, and at least one memory storing information about a plurality of chatbots and a plurality of categories of the chatbots. The memory may further store instructions that, when executed, cause the processor to receive from a client device including a user interface (UI), data associated with a voice-based or text-based user input associated with or indicative of a request to perform at least one task, to select at least one chatbot from the plurality of chatbots for at least one category for performing the at least one task among the plurality of categories of the plurality of chatbots, and to transmit information on the selected at least one chatbot and the at least one category via the communication interface to the client device such that the client device provides the information through the UI.

Abstract: A method includes obtaining, using at least one processor of an electronic device, a base model trained to perform natural language understanding. The method also includes generating, using the at least one processor, a first model expansion based on knowledge from the base model. The method further includes training, using the at least one processor, the first model expansion based on first utterances without modifying parameters of the base model. The method also includes receiving, using the at least one processor, an additional utterance from a user. In addition, the method includes determining, using the at least one processor, a meaning of the additional utterance using the base model and the first model expansion.

Abstract: A speech synthesizer using artificial intelligence includes a memory configured to store a first ratio of a word classified into a minor class among a plurality of classes, a second ratio of the word which is not classified into the minor class, and a synthesized speech model and a processor configured to change a first class classification probability set of the word to a second class classification probability set, based on the first ratio, the second ratio and the first class classification probability set, and learn the synthesized speech model using the changed second class classification probability set.

Abstract: Semantic consolidation of data is disclosed. One example is a system including a data processor, a semantic relations module, and a consolidation module. The data processor identifies at least two data objects, each data object including a plurality of data elements. The semantic relations module identifies, via a processor, semantically similar data elements of the plurality of data elements. The consolidation module merges the identified semantically similar data elements via the processor, and generates a consolidated data object based on the merged data elements.

Abstract: Methods and systems for performing a language processing task include setting an angular coordinate for a vector representation of each of a set of words, based on similarity of the words to one another. A radial coordinate is set for the vector representation of each word, according to hierarchical relationships between the words. A language processing task is performed based on hierarchical word relationships using the vector representations of the words.

Abstract: A method for analyzing constituents of a material under test is disclosed. The method includes obtaining a plurality of impedance spectroscopy measurements of the material under test over a predetermined frequency range. A data set is passed to a machine learning system, the machine learning system having been trained to return an output related to one or more constituents in the material under test based on impedance spectroscopy measurement data over the predetermined frequency range. An output of the machine learning system is received and outputted. Related systems, methods and devices are also disclosed.

Abstract: Systems and methods for automatic generation of templates for information extraction rules to extract information objects from natural language texts.

Abstract: A system and method are disclosed, to distinguish fraudulent transactions from a legitimate transaction, predicated on the notion that the card is considered likely to be in state of fraud. The disclosed system and method can be activated as soon as an account has suspicious activity that causes a high score for potential fraud, but before a bank either can or needs to confirm fraud. The system or method is able to pinpoint the actual fraudulent transactions inside a window of potential fraudulent activity, using a specialized model referred to as the pinpoint model.

Abstract: Techniques are disclosed for processing natural language communications. A computing device receives a set of natural language communications. The computing device generates a word index from the communications and generates, from the word index, a set of topics, each topic including two or more words. For each topic, the computing device generates a score indicative of an amount of semantic information represented by the topic. The computing device then discards topics that are supersets or subsets of other topics. The computing device presents the remaining topics based on to the score of each topic.

Abstract: The present invention provides a method and a system utilizing an AI entity for confirming an agreement has been entered between a first entity and a second entity during a verbal communication, capturing the portions of the communication that constitute the elements of an agreement and storing the portions for later verification of the agreement.

Abstract: An information processing device includes a divider and an identifier. The divider divides a plurality of sentences included in a processing target sentence set into a plurality of groups based on a supervised topic list representing a list of supervised topic name that is set in advance. The identifier identifies a topic name for each of the groups based on the supervised topic list.

Abstract: A system to convert sequences of human thought representations into coherent stories, in association with a language understanding system is disclosed. Said system comprises: an entity dereferencing and enrichment module, an anomaly detecting unit that comprises: a context anomaly module, and a meaning anomaly and reinforcement module; an inter thought representation reasoning and transformation unit; an entity knowledge base; a thought representation knowledge base; and an output thought representation cloud. The system takes sequences of thought representations as input and tries to make sense out of them. The system is used in association with any type of language understanding system for creating meaning out of the sequence of thoughts.

Abstract: In one embodiment, a method includes receiving a first user input by a first user at a client system associated with the first user, wherein the first user input is associated with a first language register, selecting a first language-register model from a plurality of language-register models based on the first language register by the client system, wherein the plurality of language-register models are each personalized with respect to the first user, and presenting a personalized first communication content generated based on the selected first language-register model at the client system.

Abstract: An unidentified media content item may be received by a processing device. A set of features of the unidentified media content item may be determined. Metadata associated with the unidentified media content item may be determined. A first similarity between the metadata associated with the unidentified media content item and additional metadata associated with a known media content item from a media content repository may be determined. A second similarity between the set of features of the unidentified media content item and an additional set of features associated with the known media content item may be determined. The unidentified media content item may be identified as a cover of the known media content item based on the first similarity and the second similarity by the processing device.

Abstract: An article generation method and device, and a computer storage medium. According to an example of the method, after a content source is mined based on requirement information inputted by a user, at least one topic dimension vector may be extracted from the mined content source by using a particular topic generation model. Then, for each extracted topic dimension vector, topic sentence mining is performed on the content source according to the topic dimension vector, to obtain topic sentences corresponding to the topic dimension vector. Finally, the topic sentences corresponding to the at least one topic dimension vector are spliced and synthesized, to generate an article conforming to the requirement information.

Abstract: The technology described herein provides for a match fix-up stage that removes matching documents identified for a search query that don't actually contain terms from the search query. A representation of each document (e.g., a forward index storing a list of terms for each document) is used to identify valid matching documents (i.e., documents containing terms from the search query) and invalid matching documents (i.e., documents that don't contain terms from the search query). Any invalid matching documents are removed from further processing and ranking for the search query.

Abstract: Techniques for limiting natural language processing performed on input data are described. A system receives input data from a device. The input data corresponds to a command to be executed by the system. The system determines applications likely configured to execute the command. The system performs named entity recognition and intent classification with respect to only the applications likely configured to execute the command.

Abstract: Embodiments may provide techniques to generate training data for summarization of complex documents, such as scientific papers, articles, etc., that are scalable to provide large scale training data. For example, in an embodiment, a method may be implemented in a computer system and may comprise collecting a plurality of video and audio recordings of presentations of documents, collecting a plurality of documents corresponding to the video and audio recordings, converting the plurality of video and audio recordings of presentations of documents into transcripts of the plurality of presentations, generating a summary of each document by selecting a plurality of sentences from each document using the transcript of the that document, generating a dataset comprising a plurality of the generated summaries, and training a machine learning model using the generated dataset.

Abstract: Embodiments are directed to organizing conversation information. Two or more machine learning (ML) models and a plurality of sentences provided from a conversation may be employed to generate insight scores for each sentence such that each insight score correlates to a probability that its sentence includes one or more of an action or a question. In response to one or more sentences having insight scores that exceed a threshold value an information score and a definiteness score may be determined for the one or more sentences. And one or more insights associated with the conversation may be generated based on the one or more sentences. A report may be generated that associates the one or more insights with one or more portions of the conversation that include the one or more sentences that are associated with the insights.

Abstract: A boundary of a highlight of audiovisual content depicting an event is identified. The audiovisual content may be a broadcast, such as a television broadcast of a sporting event. The highlight may be a segment of the audiovisual content deemed to be of particular interest. Audio data for the audiovisual content is stored, and the audio data is automatically analyzed to detect one or more audio events indicative of one or more occurrences to be included in the highlight. Each audio event may be a brief, high-energy audio burst such as the sound made by a tennis serve. A time index within the audiovisual content, before or after the audio event, may be designated as the boundary, which may be the beginning or end of the highlight.

Abstract: In one embodiment, a method includes receiving a first user input by a first user at a client system associated with the first user, wherein the first user input is associated with a first language register, selecting a first language-register model from a plurality of language-register models based on the first language register by the client system, wherein the plurality of language-register models are each personalized with respect to the first user, and presenting a personalized first communication content generated based on the selected first language-register model at the client system.

Abstract: Input context for a statistical dialog manager may be provided. Upon receiving a spoken query from a user, the query may be categorized according to at least one context clue. The spoken query may then be converted to text according to a statistical dialog manager associated with the category of the query and a response to the spoken query may be provided to the user.

Abstract: Method for managing a promises management apparatus comprises automatically transcribing, using an automatic speech recognition engine, a call between a caller and an agent, based on real-time call stream of the call, wherein the caller calls the agent for resolution of a concern using the promises management apparatus. The method comprises automatically extracting, using a natural language processing engine, in real-time a promise made by the agent to the caller based on the transcript of the call, generating promises data by assigning an agent, a type, a timeline, an action, and a mode of execution to the promise, and storing the promises data in a datastore.

Abstract: Methods, systems, and apparatus for receiving user input that invokes digital assistant functionality; obtaining screen data indicating content displayed on a screen of the computing device; determining a classification for an entity referenced in the content indicated by the screen data; determining a suggested request that refers to the entity based on the determined classification; and providing the suggested request in response to receiving the user input that invokes the digital assistant functionality.

Abstract: A method for expanding software application functionalities processing is disclosed herein. The method comprises receiving a user request within a software application. The software application is enhanced with annotations, which include metadata. The method continues with loading the metadata from the annotations to a dialog system located on a remote device, sending at least a part of the user request to the dialog system, and receiving a dialog system response to the user request from the dialog system. At least one of the annotations associated with the dialog system response is identified. A code associated with the identified annotation is invoked within the software application.

Abstract: Users consume a wide variety of content from various sources, such as videos accessible through websites. As provided herein, content recommendations that are contextually and/or semantically relevant to current content consumed by a user may be identified and provided to the user. For example, metadata for a video being watched by the user may be identified (e.g., terms extracted from a description, user reviews, a category, and/or other information). The metadata may be used to identify content recommendations based upon the metadata corresponding to terms grouped into a set of refined topic groupings of a graph comprising terms and relationships between terms extracted from a content corpus. The metadata may be matched to relevant terms within the set of refined topic groupings, and content recommendations comprising content corresponding to the relevant terms may be suggested to the user.

Abstract: Methods, systems, and computer-readable media for generating a statistically covaried machine learning model for performance measurement of service providers. The method receives a configuration file that includes one or more parameters associated with a plurality of individuals and parses it to generate and executing the database query on input data to generate sets of tabulated data of individuals of the plurality of individuals. The method next determines one or more measures of service providers listed in the configuration file using two or more tabulated data of individuals from the sets of tabulated data of individuals. The method finally generates a covaried machine learning model by training a machine learning model by statistically covarying measures and using them as training data.

Abstract: Techniques and systems are provided for authenticating a user of a device. For example, input biometric data associated with a person can be obtained. A similarity score for the input biometric data can be determined by comparing the input biometric data to a set of templates that include reference biometric data associated with the user. The similarity score can be compared to an authentication threshold. The person is authenticated as the user when the similarity score is greater than the authentication threshold. The similarity score can also be compared to a learning threshold that is greater than the authentication threshold. A new template including features of the input biometric data is saved for the user when the similarity score is less than the learning threshold and greater than the authentication threshold.

Abstract: Various embodiments set forth a method for automatically configuring a multi-chassis link aggregation group (MLAG), including receiving first system information associated with the MLAG, receiving a first discovery packet via a first uplink port associated with a first switch that is included in the MLAG, where the first discovery packet includes second system information associated with the MLAG, determining whether the first system information matches the second system information, where if the first system information matches the second system information, then concluding that the first uplink port is included in an inter peer link connecting the first switch to a second switch that also is included in the MLAG, and if the first system information does not match the second system information, then concluding that the first uplink port is not included in the inter peer link. Advantageously, the method avoids requiring a user to enter hundreds of commands manually.

Abstract: A speech translation apparatus includes: an estimator which estimates a sound source direction, based on an acoustic signal obtained by a microphone array unit; a controller which identifies that an utterer is a user or a conversation partner, based on the sound source direction estimated after the start of translation is instructed by a button, using a positional relationship indicated by a layout information item stored in storage and selected in advance, and determines a translation direction indicating input and output languages in and into which content of the acoustic signal is recognized and translated, respectively; and a translator which obtains, according to the translation direction, original text indicating the content in the input language and translated text indicating the content in the output language. The controller displays the original and translated texts on first and second display areas corresponding to the positions of the user and conversation partner, respectively.

Abstract: Provided is a method including obtaining a corpus and an associated set of domain indicators. The method includes learning a set of vectors in an embedding space based on n-grams of the corpus. The method includes updating ontology graphs comprising a set of vertices and edges associating the set of vertices with each other. The method also includes determining a vector cluster using hierarchical clustering based on distances of the set of vectors with respect to each other in the embedding space and determining a hierarchy of the ontology graphs based on a set of domain indicators of a respective set of vertices corresponding to vectors of the vector cluster. The method also includes updating an index based on the ontology graphs.

Abstract: Disclosed herein are system, method, and computer program product embodiments for recognizing a human emotion in a message. An embodiment operates by receiving a message from a user. The embodiment labels each word of the message with a part of speech (POS) thereby creating a POS set. The embodiment determines an incongruity score for a combination of words in the POS set using a knowledgebase. The embodiment determines a preliminary emotion detection score for an emotion for the message based on the POS set. Finally, the embodiment calculates a final emotion detection score for the emotion for the message based on the preliminary emotion detection score and the incongruity score.

Abstract: A method, system and computer-usable medium are disclosed for reducing labeled data imbalances when training an active learning system. The ratio of instances having positive labels or negative labels in a collection of labeled instances associated with an input category used for learning is determined. A first instance for annotation is selected from a collection of unlabeled instances if a first threshold for negative instances, and a first threshold confidence level of being a positive instance of the input category, have been met. A second instance for annotation is selected if a second threshold for positive instances, and a second threshold confidence level of being a negative instance of the input category, have been met. The first and second instances are respectively annotated with a positive and negative label and added to the collection of labeled instances, which are then used for training.

Abstract: Techniques are described for providing information during a service session, using an intelligent agent. The intelligent agent executes as a process to monitor communications exchanged during a service session between an individual and a service representative (SR) within a service environment. The agent analyzes the communications to identify questions or other topics that are posed by the individual during the service session. The agent retrieves stored data related to such questions or other topics, and generates a message to address each question or other topic. The message is injected into the service session to be presented to the individual, to supplement the conversation that is taking place between the SR and the individual. In some implementations, the agent monitors the communications, generates the message, and/or injects the message into the service session at least partly autonomously of any explicit action taken by the SR.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for managing dialogs. In one aspect, a method includes receiving a request associated with a task from a user device; submitting the request to each of a plurality of distinct data providers; receiving a plurality of suggested dialog responses from two or more of the data providers; scoring the one or more suggested dialog responses based on one or more scoring factors; determining a particular dialog response to provide to the user based on the scoring; and providing the determined dialog response to the user device.

Abstract: A facility for representing a mandate occurring in an authority document with a control is described. For each of one or more controls in a set of existing controls, the facility determines a similarity score measuring the similarity of the mandate and the control; where the similarity score exceeds a similarity threshold, the facility links the mandate to the control. Where the mandate is not linked to any control in the set of controls, the facility adds a control to the set of controls that is based on the mandate, and links the mandate to the added control.

Abstract: A method includes displaying a suggestion region above an on-screen keyboard. The suggestion region includes multiple suggested character strings. The method further includes: detecting a gesture that begins within a predefined key of the on-screen keyboard; and responsive to detecting the gesture: in accordance with a determination that the gesture ends within the predefined key, inserting a first character string into a text field; and in accordance with a determination that the gesture ends outside of the predefined key, inserting a second character string into the text field, wherein the second character string is different from the first character string.

Abstract: Disclosed herein are system, method, and computer program product embodiments for training a machine learning model and using the machine learning model to determine an intent associated with an utterance. An embodiment operates by receiving an utterance, determining a first vector based on the received utterance, and determining a second vector based on the received utterance. A third vector is generated by concatenating the first vector and the second vector. The third vector is used to perform at least one of classifying, using a machine learning model, the utterance to determine the intent associated with the utterance or training the machine-learning model.

Abstract: The present invention is a system and method for optimizing the narrative text generated by one or more narrative frameworks that utilize data input from one or more data sources to drive the creation of a narrative text output. Narrative text is generated in accordance with sets of data that provide the scope of text to be generated. A Quality Assurance module presents the narrative text output to a user that reviews both the condition and the logic evaluation associated with the scope, and the quality of the generated text. A log of Quality Assurance items is created upon review of the generated text. These items are then later resolved by locating them in a narrative text generation data structure to resolve the identified issues.