Abstract: Embodiments of this disclosure include an encoding method and apparatus. The encoding may include obtaining a target paragraph and a context sentence of the target paragraph, and inputting the target paragraph and the context sentence into a memory encoding model. The encoding may further include obtaining an original vector set and a memory vector set in the input layer and obtaining a first target sentence matrix of the original vector set in the memory layer according to the original vector set and the memory vector set. The encoding may further include obtaining a paragraph vector of the target paragraph in the output layer according to the first target sentence matrix and performing processing based on the paragraph vector.

Abstract: A method increases user interaction with deep learning agents. A generation request for a content slot is received. A subsequent tag vector, for the content slot, is generated from a previous tag, for a previous content slot, using a subsequent tag model. A context vector is generated from a set of subsequent tag vectors, which include the subsequent tag vector, using a context vector generator. A selection vector is generated from the context vector using a contextual bandit model. A content set is generated for a content slot using the selection vector. The content set for the content slot is presented.

Abstract: A media recommendation system may score media items according to user recommendations, popularity, and/or recency. The scores may be weighted to produce an overall score for each media item. Media items may be added to a pool for a specific user, from which media items are selected for playback. The contents of the pool may be modified based upon user feedback and other data. The pool may be modified dynamically and/or in real time as media items are consumed or rated by the user.

Abstract: Systems, methods, and computer readable media related to: training an encoder model that can be utilized to determine semantic similarity of a natural language textual string to each of one or more additional natural language textual strings (directly and/or indirectly); and/or using a trained encoder model to determine one or more responsive actions to perform in response to a natural language query. The encoder model is a machine learning model, such as a neural network model. In some implementations of training the encoder model, the encoder model is trained as part of a larger network architecture trained based on one or more tasks that are distinct from a “semantic textual similarity” task for which the encoder model can be used.

Abstract: A media recommendation system may score media items according to user recommendations, popularity, and/or recency. The scores may be weighted to produce an overall score for each media item. Media items may be added to a pool for a specific user, from which media items are selected for playback. The contents of the pool may be modified based upon user feedback and other data. The pool may be modified dynamically and/or in real time as media items are consumed or rated by the user.

Abstract: A fuzzy matching system matching data records in one or more data sets based on user-customized selection of multiple fuzzy matching algorithms. Possible matches may be displayed to a user, who provides feedback on the accuracy of the matches, which may then be used by a machine learning algorithm to update weightings and parameters of the multiple fuzzy matching algorithms, such as based on machine learning analysis of the matching results and the user feedback.

Abstract: A method for providing contextual analytics of target information by using similarity mapping is disclosed. The method includes retrieving, via a communication interface, raw data from several sources based on a predetermined characteristic of the raw data, the raw data including natural language data; receiving, via a graphical user interface, a target document; converting, by using a natural language processing technique, the raw data into structured data based on a predetermined parameter; refining the target document to generate a target data set; generating a structured data set from the structured data by using a dimensionality reduction technique; and displaying, via the graphical user interface, a graphical element, the graphical element including a similarity plot of the structured data set and the target data set.

Abstract: Provided are a question answering method and language model training method, apparatus, device, and storage media, including: acquiring at least one candidate table matching a question to be queried, each candidate table includes a candidate answer corresponding to the question; processing the at least one candidate table to obtain at least one table text, the table text includes textual content of respective fields in the candidate table; inputting the question and each table text into a preset language model respectively to obtain a degree of matching between the question and each candidate table; and outputting a reply table according to the degree of matching of each candidate table, the reply table is a candidate table out of the at least one candidate table whose degree of matching with the question is greater than a preset value or a candidate table that corresponds to a maximum degree of matching.

Abstract: Introduced here are various embodiments for selectively assigning a query to an expert. A network-accessible server system may receive a query from a client device indicating a question or project proposal. The query text may be parsed and attributes of the query may be determined by inspecting the parsed query text. The query attributes may be compared with attributes associated with a pool of experts with various specialties and expertise in various fields. The network-accessible server system may match the query attributes with attributes associated with a first expert with a similarity that exceeds a threshold similarity level to identify that an expertise of the first expert matches the requested expertise in the query. The first expert may be assigned to the query and prompted to provide a response to the query.

Abstract: A media recommendation system may score media items according to user recommendations, popularity, and/or recency. The scores may be weighted to produce an overall score for each media item. Media items may be added to a pool for a specific user, from which media items are selected for playback. The contents of the pool may be modified based upon user feedback and other data. The pool may be modified dynamically and/or in real time as media items are consumed or rated by the user.

Abstract: An apparatus includes a processor and a machine-readable medium having program code to cause the apparatus to obtain a first dictionary based on a first training set of signals and determine a first subset of the first training set of signals based on a training reconstruction accuracy threshold and the first dictionary, wherein each atom in the first dictionary includes at least one of a signal pattern and a function representing the signal pattern. The program code also includes code to generate a second dictionary based on a second training set of signals, wherein the second training set of signals includes the first subset of the first training set of signals.

Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.

Abstract: A location extraction component analyzes a set of travelogues to identify all of the locations mentioned therein. A co-occurrence extraction component computes co-occurrence values for the identified locations. When the identity of a specified location is received, suggested locations for the specified location are identified through the use of the co-occurrence values. A map is displayed that encompasses an area including the specified location and the suggested locations. The map might include indicators for the specified location and for each of the suggested locations. Attributes of the indicators, such as their size or color, can be modified based upon the co-occurrence value associated with the corresponding suggested location.

Abstract: Methods and systems for detecting anomalies in sets of data are disclosed, including: computing components of one or more types of feature vectors at a plurality of values of one or more independent variables, each type of the feature vectors characterizing a set of input data being dependent on the one or more independent variables; computing one or more types of output values corresponding to each type of feature vectors as a function of the one or more independent variables using a nonlinear sequence analysis method; and detecting anomalies in how the one or more types of output values change as functions of the one or more independent variables.

Abstract: An indexing database utilizes a non-transitory storage medium. A pattern matching processing unit generates preclassification data for the network data packets utilizing pattern matching analysis. At least one processing unit implements a storage process that receives the network data packets, stores the network data packets in at least one of the slots, and transfers the network data packets to a packet capture repository when slots in a shared memory are full. A preclassification process requests from the pattern matching processing unit the preclassification data. An indexing process determines, based upon the preclassification data, whether to invoke or omit additional analysis of the network data packets, and performs at least one of aggregation, classification, or annotation of the network data packets in the shared memory to maintain one or more indices in the indexing database.

Abstract: The relevance of an object, such as a document resulting from a query, may be determined automatically. A graphical model-based technique is applied to determine the relevance of the object. The graphical model may represent relationships between actual and observed labels for the object, based on features of the object. The graphical model may take into account an assumption of noisy training data by modeling the noise.

Abstract: A system that enables development and execution of predictive models comprises a centralized data management system, a data extraction tool a model validation tool and a model execution tool. In embodiments, a data management system includes a data management server that can be accessed via a web browser that stores data. An extraction tool includes a data filter adapted to filter data based on, for example, a population criteria, a sample size, and a date range criteria. A model validation tool validates the model. A model execution tool allows a user to score the model.

Abstract: A data storage system includes a network interface configurable to couple to a network for receiving data related to an acoustic environment from a device and a memory for storing a plurality of environmental filters. The data storage system further includes a processor coupled to the memory and the network interface, the processor configurable to analyze the data and selectively provide one or more of the plurality of environmental filters to the device based on the analysis of the data.

Abstract: A system, method, and apparatus for information retrieval are provided. Embodiments of the present invention may generate data structures that may be used to process user queries. According to embodiments of the present invention, a processor component configured to perform the operations of an indexing module and a storage module, the indexing module configured to generate a term list and a term-file matrix from information stored on the storage module, the indexing module further configured to generate an adjacency matrix from the one or more files, wherein the adjacency matrix represents a relationship of the one or more terms in each of the one or more files; and the indexing module further configured to generate a probability matrix using the adjacency matrix and a one-step or two-step random walk.

Abstract: System for providing a mobile user, object related information related to an object visible thereto, the system including a camera directable toward the object, a local interest points and semi global geometry (LIPSGG) extraction processor, and a remote LIPSGG identifier, the camera acquiring an image of at least a portion of the object, the LIPSGG extraction processor being coupled with the camera, the LIPSGG extraction processor extracting an LIPSGG model of the object from the image, remote LIPSGG identifier being coupled with the LIPSGG extraction processor via a network, the remote LIPSGG identifier receiving the LIPSGG model from the LIPSGG extraction processor, via the network, the remote LIPSGG identifier identifying the object according to the LIPSGG model, the remote LIPSGG identifier retrieving the object related information, the remote LIPSGG identifier providing the object related information to the mobile user operating the camera.

Abstract: The present invention provides a method and system for extending content based on the semantic meaning of content. It divides content into multiple content regions and finds words and/or phrases that are semantically relevant to the current content region and appends these words and/or phrases to the current content region as extended content. The extended content matches semantically with the original content in such a seamless way that users may think it is a part of the content.

Abstract: The method according to one embodiment of the present invention comprises retrieving one or more terms or phrases comprising an instant messaging conversation in which one or more users are participating. One or more term vectors comprising one or more vector terms associated with the one or more retrieved terms or phrases comprising the instant messaging conversation are generated and one or more vector terms are selected from said term vectors. The one or more selected vector terms are displayed to the one or more users participating in the instant messaging conversation. An indication of a user selection of a given displayed vector term is received and one or more content items responsive to the selected vector term are identified.