Robert Boschgmbh

Sap Se

Lin Zhao

Zhe Feng

Fuliang Weng

Kui Xu

Yifan He

Fei Liu

Ting Wang

Jian Li

Doo Soon Kim

Zhongnan Shen

Haibo Ding

Jun Araki

Guoliang Li

Zhiqian Ding

Wenchang Zhang

Lishi Shen

Sai Wu

Linfeng Song

Chao Shen

Haibin Yuan

An automatic terminology linking system includes a candidate generator configured to identify candidate nodes for each terminology that is to be linked to a node of the knowledge base. A pseudo-candidate generator is configured to identify pseudo-candidate nodes for candidate-less terminologies. A candidate scorer is configured to respectively score the candidate nodes and the pseudo-candidate nodes by collective inference using occurrence statistics and co-occurrence statistics for these nodes. The pseudo-candidate generator is configured to identify knowledge base nodes that are semantically-related to candidate-less terminology as the pseudo-candidate nodes for the candidate-less terminology.

System and method for domain-independent terminology linking

A method of automatically generating a terminology definition knowledge base (KB) includes mapping each word in a word sequence to a real value dense vector using dense vector representations. The word sequence is then processed using a Convolutional Neural Network (CNN) model to identify whether the word sequence includes a terminology definition and to label the word sequence with a label indicating whether a terminology definition exists within the word sequence. The word sequence is then processed using a Conditional Random Field (CRF) model to identify boundaries of the terminology definition in the word sequence. The terminology definition is then extracted and added to the terminology definition KB.

System and method for domain- and language-independent definition extraction using deep neural networks

A server includes a controller in communication with the server and configured to receive a query related to an issue with a vehicle, retrieve information related to the query from a database that includes structured data including data related to vehicle issues and a solution to the vehicle issues, determine whether the database includes structured data including data related to the solution responsive to the query, and output information including the solution to the issue when the determination identifies that the structured data including the solution in the database or retrieve information from a website when the determination identifies that the structured data including the solution is not found in the database, wherein the controller is further configured to retrieve the information from the website by conducting a keyword search for a first set of results and filtering the information from the website utilizing an autoencoder.

System and method for information extraction and retrieval for automotive repair assistance

A system can receive an identifier for a query used by a query service of one or more query services and an identifier for the query used by an issuing computer system. The query service and the computer system that issued the query can use different schemas for query results. A mapping can be established that maps elements of one schema to the other schema. This mapping, and a mapping of the query identifiers, can be used to convert query results to a format useable by the computing system that issued the query. By converting query results from multiple query services, which may have different formats, to a common format of the issuing computing system, the use of multiple query services is facilitated.

Retrieval and conversion of query results from multiple query services

DIY (Do-It-Yourself) is challenging for many novices, requiring extensive knowledge such as the usage of particular tools and the properties of the required materials. Many DIYers use web searches to find relevant information and instructions, but web search is time-consuming and the results often do not fit the DIYers' specific needs. To address these problems, we present a Question Answering (QA) system that can assist DIYers through the whole cycle of a DIY project. Given a natural language question about a DIY project, the QA system described herein provides an answer along with the explanations that are tailored to the DIYers' specific needs.

Knowledge-based question answering system for the DIY domain

A method for slot-filling in an automated spoken language understanding (SLU) system includes receiving words in a text phrase, generating an encoded output and attention weights using a recurrent neural network (RNN) encoder with an attention mechanism, generating a first and second probability distributions of slot words in an extended slot vocabulary database using an RNN decoder and a pointer network, respectively, for a time step, generating a combined probability distribution based on the first and second probability distributions, and identifying a slot word corresponding to one word in the extended slot vocabulary database having a highest probability value in the combined probability distribution for the time step.

Slot filling in spoken language understanding with joint pointer and attention

A method for automated aspect-based sentiment analysis includes parsing reviews from a first domain to generate rhetorical structure trees and extracting rhetorical rules from the rhetorical structure trees, each rhetorical rule including a path extracted from at least one span in at least one of the rhetorical structure trees associated with a probability that the path corresponds to a positive or negative sentiment based on annotation data. The method further includes parsing reviews from a second domain to generate a second plurality of rhetorical structure trees, generating training data that associates at least one aspect in the review from the second domain with a sentiment associated with a rhetorical rule in the plurality of rhetorical rules, and training a classifier to identify sentiments in reviews from the second domain using the second plurality of reviews and the training data.

System and method for domain-independent aspect level sentiment detection

A method of generating a question data set from a knowledge base including a plurality of statements includes generating at least one question template based on a structure of selected statements of the plurality of statements, generating a seed question for each selected statement based on the at least one question template with a processor, generating at least one first extension question with a search engine by processing each of the seed questions through the search engine, and storing at least one of the at least one first extension questions and the seed questions in a memory as the question data set.

System and method for automatic question generation from knowledge base

A method for processing messages pertaining to an event includes receiving a plurality of messages pertaining to the event from electronic communication devices associated with a plurality of observers of the event, generating a first message stream that includes only a portion of the plurality of messages corresponding to a first participant in the event, identifying a first sub-event in the first message stream with reference to a time distribution of messages and content distribution of messages in the first message stream, generating a sub-event summary with reference to a portion of the plurality of messages in the first message stream that are associated with the first sub-event, and transmitting the sub-event summary to a plurality of electronic communication devices associated with a plurality of users who are not observers of the event.

System and method for event summarization using observer social media messages

An in-vehicle infotainment system, smart home information access and device control unit, or mobile system presents summarized information to a user based on a user preference model that is associated with the user. The system modifies the presentation of information to the user based on environmental context data about the vehicle and user context data about the activity of the user. During presentation of the information, the system modifies the content and presentation of the summarized information in response to multi-modal input requests from the user.

System and method for dialog-enabled context-dependent and user-centric content presentation

A method for speech recognition of partial proper names is described which includes natural language processing (NLP), partial name candidate generation, speech recognition and post processing. Natural language processing techniques including shallow and deep parsing are applied to long proper names to identify syntactic units (for example, noun phrases). The syntactic units form a basis for generating a candidate list of partial names for each original full name. A partial name is part of the original name, with some words omitted, or word order changed, or even word substitution. After candidate partial names are generated, their phonetic transcriptions are incorporated into a model for a speech recognizer to recognize the partial names in a speech recognition system.

Speech recognition of partial proper names by natural language processing

In accordance with one embodiment, a method of generating language models for speech recognition includes identifying a plurality of utterances in training data corresponding to speech, generating a frequency count of each utterance in the plurality of utterances, generating a high-frequency plurality of utterances from the plurality of utterances having a frequency that exceeds a predetermined frequency threshold, generating a low-frequency plurality of utterances from the plurality of utterances having a frequency that is below the predetermined frequency threshold, generating a grammar-based language model using the high-frequency plurality of utterances as training data, and generating a statistical language model using the low-frequency plurality of utterances as training data.

Speech recognition using multiple language models

A method of statistical modeling is provided which includes constructing a statistical model and incorporating Gaussian priors during feature selection and during parameter optimization for the construction of the statistical model.

Unified treatment of data-sparseness and data-overfitting in maximum entropy modeling

A method of proper name recognition includes classifying each word of a word string with a tag indicating a proper name entity category or a non-named entity category, and correcting the tag of a boundary word of the word string.

Growing community of inventors

Sunnyvale, CA, United States of America

Lin Zhao