Abstract: A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process including determining whether first answer information has been cited in a generation process of second answer information for a first inquiry based on history information, stored in a storage device, indicating a citation histories regarding pieces of answer information, and generating training data associating the first inquiry with the first answer information when the first answer information has been cited in a generation process.

Abstract: Systems and methods for managing content provenance are provided. A network system accesses a document of a plurality of documents to be analyzed. The network system extracts text fragments from the document including a first fragment and a second fragment. A determination is made whether each of the text fragments match an entry in a hash table. Based on a first fragment not matching any entries in the hash table, the network system creates a new entry in the hash table, whereby the first fragment is used to generate a key in the hash table. Based on a second fragment matching an entry of the hash table, the network system associates the document with a key of the matching entry in the hash table, whereby the associating comprising updating the hash table with an identifier of the document.

Abstract: A method may include receiving a request to save the exception to the first rule; in response to the request, updating the user interface, wherein: the first portion is updated to include a parameter of a second rule to exclude a subset of meetings from the ECDS; the second portion is updated to include an impact metric that indicates a percentage of meetings excluded from the ECDS based on an application of the second rule to the ECDS; and the third portion is updated to include selectable elements for creating an exception to the second rule; and a fourth portion of the user interface includes an indication of a number of meetings excluded from the ECDS based on application of the first rule with any exceptions to the first rule.

Abstract: Methods for asset type fingerprinting are provided. An example method involves an asset tracking system failing to identify an asset type fingerprint and requesting an asset type fingerprint from an asset data analysis system. The asset data analysis system generates a proposed asset type fingerprint, links the asset type fingerprint to a set of signal definitions that indicate how to decode data messages from the asset. The asset data analysis system transmits the proposed asset type fingerprint to the asset data analysis system, which then decodes at least some data messages from the asset thus obtaining asset information. The method may be used to identify vehicle types and decode proprietary or non-standard data messages via a vehicle's diagnostic port.

Abstract: A server may include a communication circuit, at least one processor electrically connected to the communication circuit, and at least one memory electrically connected to the at least one processor. The at least one memory stores instructions for receiving, from a first external device, first data related to a user input that requests performance of a task, receiving, second data associated with a plurality of application programs, determining a domain related to the task based on at least some of the first data and at least some of the second data, determining a likely intention of a user providing the user input, based on at least some of the first data, and determining a sequence of states of the first external device based on the domain and the likely intention, providing the sequence of states to the first external device.

Abstract: An object of the present invention is to provide a reliable supplier evaluation system for correctly evaluating suppliers. A supplier evaluation system 117 according to the present invention is a system for evaluating suppliers based on information relating to a transaction conducted between a buyer and the supplier. The supplier evaluation system 117 is provided with a reception function for receiving communication information 134 and e-commerce information conducted between a buyer and a supplier and that exists in a company system such as that of a buyer, a conversion function for converting the communication information and the e-commerce information into a predetermined format, a database 133 for storing keyword information, and an analysis function 127 for comparing keyword information 138 registered in advance in a storage device with the converted communication information and e-commerce information, and determining a cause of a transaction result of the e-commerce information.

Abstract: Systems and methods to identify a filter set in a keyword query are described. The system receives a query from a client machine. The system identifies filter sets based on the query and a based on rules. The filter sets include a first filter set that includes a first filter. The rules are utilized to associate at the least one keyword from the query to the first filter. The system further scores the filter sets based on probabilities to generate scores. The probabilities describe occurrences of attribute-value pairs in listings that respectively describe items that were previously transacted on a network-based marketplace. The system further identifies the first filter set from the filter sets based on the scores, generates a user interface including search results that are identified based on the identified first filter set, and communicates the user interface, over the network, to the client machine.

Abstract: Techniques and tools are described for producing time-series data using faceted search based on document creation time. For example, index information can be created from events (e.g., by adding meta-data and indexing the events as documents). In addition, index information can be created that maps document creation time to time ranges. Search queries can then be executed (e.g., comprising ad-hoc filters to filter on the meta-data), and search results can be faceted on the time ranges to produce time-series data. The time-series data can be graphed to display trends of activity (e.g., trends of events based on user activity).

Abstract: Disclosed are methods, systems, and non-transitory computer-readable record mediums for processing a chatroom based on a level of use. A chatroom processing method including verifying a level of use by a user with respect to each chatroom of chatrooms included in a chatroom list, selecting at least one chatroom from the chatroom list as a chatroom to be managed based on the level of use, and processing the chatroom to be managed to be distinguished from remaining chatrooms in the chatroom list may be provided.

Abstract: Methods, systems, and computer program products for dynamically analyzing diagnostic operations data via machine learning techniques are provided herein. A computer-implemented method includes defining aspects of machine learning techniques to be performed in connection with diagnostic operation data analysis, including: defining dynamic analysis granularity selection functionality based on time constraints and the level of progress of the analysis; defining dynamic data classification identifier type selection functionality based on the time constraints and the level of progress of the analysis; and defining dynamic ordering of data classification identifiers during runtime based on data classification preferences, information pertaining to system workload, and information pertaining to requested analysis compliance parameters.

Abstract: A computer-implemented method of answering questions comprises: receiving, by one or more processors, a query; based on the query, generating, by the one or more processors, a matrix; based on the matrix, modifying, by the one or more processors, a dynamic memory; based on the matrix, determining, by the one or more processors, a first response from the dynamic memory; based on the matrix, determining, by the one or more processors, a second response from a database; based on the first response and the second response, determining, by the one or more processors, a third response; and in response to the query, providing, by the one or more processors, the third response.

Abstract: Example embodiments described herein pertain to a geospatial interface system configured to cause display of geospatial data within a graphical user interface at a client device, receive data points from multiple data sources, unify the data points, and present the unified data points as interactive graphical elements within the graphical user interface, in a presentation layer separate from the geospatial data. In example embodiments, the geospatial interface system may be or include a group of one or more server machines configured to provide one or more geospatial data display, indexing, and management services. A client device may accordingly display a graphical user interface generated by the geospatial interface system.

Abstract: Techniques for solving a multi-agent plan recognition problem are provided. In one example, a computer-implemented method comprises transforming, by a device operatively coupled to a processor, a problem model and an at least partially ordered sequence of observations into an artificial intelligence planning problem through a transform algorithm. The problem model can comprises a domain description from a plurality of agents and a durative action. Furthermore, at least one of the observations of the at least partially ordered sequence of observations can be a condition that changes over time. The computer-implemented method further comprises determining, by the device, plan information using an artificial intelligence planner on the artificial intelligence planning problem. The computer-implemented method further comprises translating, by the device, the plan information into information indicative of a solution to the artificial intelligence planning problem.

Abstract: The described implementations are operable to determine potential objects of interest to a user based on a blend of the user's long-term behavior and short-term interests. Long term user behavior may be determined for the user over a period of time and represented as continuous data. Short-term interest may be determined based on objects with which the user has recently interacted and attributes of those objects may be represented together as continuous data corresponding to the short-term user interest. The continuous data of the short-term interest and long-term user behavior may be blended to produce a user embedding. The user embedding may then be compared with objects to determine objects that are of potential interest to the user.

Abstract: Example implementations described herein are directed to a meta-data processing system that supports the creation and deployment of the Analytical Solution Modules in development of industrial analytics. The example implementations described herein can involve a first system configured to be directed to a data scientist for receiving flow and operator definitions to generate an analytics library, which is provided to a second system configured to be directed to a domain expert for applying the analytics library to generate analytics modules to be executed on data input to the second system.

Abstract: Embodiments also include a method for filtering and securing content of datasets in computer readable form designated for release to reduce discernable inferences therein. The method includes receiving a first dataset having first records associated with a quasi-identifier. The first records have respective first data values associated with the quasi-identifier. The method includes receiving a second dataset having second records associated with the quasi-identifier. The second records have respective second data values associated with the quasi-identifier. The method includes defining a first cluster having a first boundary based on a combination of the first dataset and the second dataset. The method includes replacing a first one of the first data values with the first boundary and a second one of the second data values with the first boundary.

Abstract: Methods and systems for estimating recall while screening an ordered list of bibliographic references are provided. According to one embodiment, a method includes: sorting a list of bibliographic references according to a sorting algorithm to produce a first list in order from most to least relevant; selecting, from the list, the most relevant reference, and displaying, to a human screener, information associated with the selected reference; and receiving the screener's judgment of the relevance of the selected reference. If sufficiently relevant, the selected reference is moved from the first list to a second list. The received indication is used to re-sort the remaining references in the first list. A statistical model is used to estimate the number of relevant references remaining. That estimate is displayed to the screener. The process ends when the screener determines, based on the displayed estimate, that a sufficient number of relevant references has been found.

Abstract: A database may contain representations of: (i) software packages managed by a software management tool, including publishers, titles, and categories associated with each, and (ii) a plurality of software activities, including descriptions and amounts associated with each. A server device may be configured to obtain classifications of the software activities that predict the publishers, titles, and categories of the software activities from the descriptions. The server device may further compare the software packages to the classifications in order to identify: (i) unmanaged software packages, and (ii) amounts associated with the software packages.

Abstract: Computer vision for unsuccessful queries and iterative search is described. The described system leverages visual search techniques by determining visual characteristics of objects depicted in images and describing them, e.g., using feature vectors. In some aspects, these visual characteristics are determined for search queries that are identified as not being successful. Aggregated information describing visual characteristics of images of unsuccessful search queries is used to determine common visual characteristics and objects depicted in those images. This information can be used to inform other users about unmet needs of searching users. In some aspects, these visual characteristics are used in connection with iterative image searches where users select an initial query image and then the search results are iteratively refined.

Abstract: In an implementation, a non-transitory machine-readable storage medium stores instructions that when executed by a processor, cause the processor to allocate classifier data structures to persistent memory, read a number of categories from a set of training data, and populate the classifier data structures with training data including training-based, category and word probabilities calculated based on the training data.

Abstract: A method, a computing system and a computer program product are provided. A model is generated and trained. The model is based on clinical data with outcomes from clinically-defined hierarchical metadata in a selected level of clinically-defined hierarchical metadata serving as an initial set of prediction targets. A score is determined for each of the prediction targets based on the generated model and the set of evaluation factors. The set of prediction targets, the generated model, and the scores for the set of prediction targets are updated until the updated scores for the updated set of prediction targets satisfy acceptance criteria. The updated generated model, using the updated set of prediction targets, is applied to predict one of a set of updated prediction targets of mutually exclusive outcome categories.

Abstract: A method, system, and program product for implementing intelligent cache preloading is provided. The method includes monitoring current usage of a system of record (SOR) system. Historical data associated with historical usage of the SOR system is retrieved and analyzed based on the current usage. A ranked list of data items configured to be loaded within a cache structure of the cache system is generated and currently requested data items from the SOR system are loaded into the cache structure via a throttling process. A malfunction associated with operation of the SOR system is detected and access to the currently requested data items is enabled. The currently requested data items are organized within the cache structure in accordance with an order of the ranked list and access to the currently requested data items is enabled, during the malfunction, in accordance with the order of the ranked list.

Abstract: An online system receives information describing events corresponding to actions associated with a third party system performed by an individual. The received information describes event types and times at which the events occurred. The online system generates nodes of a directed graph associated with the third party system, in which each node corresponds to an event type. For each event, a node count associated with a node corresponding to the event's type is incremented by the online system. Pairs of consecutively occurring events are identified based on times at which the events occurred and an edge describing each transition from one event to another is generated by the online system. The online system determines an edge count for each transition indicating a number of edges describing the transition as well as a sequential order of event types based on one or more node counts and one or more edge counts.

Abstract: One embodiment provides a system for facilitating a graph search engine. During operation, the system receives, by a server from a client computing device, a search request which includes a user-inputted graph. The system performs a search based on a structure of the user-inputted graph for a plurality of relevant graphs. The system orders the plurality of relevant graphs from a most relevant ranking to a least relevant ranking. The system returns, to the client computing device, the ordered plurality of relevant graphs for display on a user interface of the client computing device, thereby enhancing the search for relevant graphs by allowing the graph search engine to take as an input the user-inputted graph and return as an output the relevant graphs.

Abstract: A computer-implemented method, system and computer program product for improving query searches. After receiving a query from a user to conduct a content search, the query is analyzed for its semantic meaning and a categorized group of query tags and content tags in the central repository that is most semantically similar in meaning to the meaning of the query is identified. Furthermore, the content tags and query tags in the user's repository are analyzed to determine the interests of the user. The query may then be augmented to include one or more other terms of interest from the identified categorized group of query tags and content tags in the central repository that match the determined interests of the user within a threshold degree of relatedness, where these other terms of interest correspond to the content tags and query tags of the identified categorized group based on their assigned weight.

Abstract: Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of training one or more first models to recommend a first item after a user has had an interaction on the web site of the online retailer with a second item, determining static features common to both the first item and the second item, training a second model to determine whether to coordinate a display of any new item as one of one or more recommended items with any of a plurality of items, and coordinating the display of the new item as one of the one or more recommended items when the one or more of the plurality of items are displayed on the website of the online retailer based on the static features of the new item.

Abstract: Systems, methods, and computer program products for associating a media content clip(s) with other media content clip(s) having a different modality by determining first embedding vectors of media content items of a first modality, receiving a media content clip of a second modality, determining a second embedding vector of the media content clip of the second modality, ranking the first embedding vectors based on a distance between the embedding vectors and the second embedding vector, and selecting one or more of the media content items of the first modality based on the ranking, thereby pairing media content clips based on emotion.

Abstract: A network data transmission method is provided. A switch device receives one or more data flows, classifies each of the received data flows into one of two classes according to data features of the data flow by using a decision tree model established by a flow table pipeline of the switch device. If a data flow belongs to a first class, the switch device reports the data flow to a controller, so that the controller computes a transmission path for the data flow. If a data flow belongs to a second class, the switch device obtains a transmission path for the data flow according to local flow table information, and transmits the data flow according to the obtained transmission path. Data flows are classified and filtered by using a switch, so as to improve network transmission efficiency while ensuring bearing capability of a network control system.

Abstract: Methods and systems for text classification include identifying a text sample, classified according to a first class in a set of hierarchical graphs of classes, that is more similar to a second class in the set of hierarchical graphs of classes than to the first class according to a similarity metric. A word is deleted from the identified text sample that is associated with the second class. A word is added to the identified text sample that is associated with the first class. A text classification model is trained using the text sample as training data. Text classification is performed on an input text using the trained text classification model implemented on a processor device.

Abstract: A method includes searching an initial set of documents for an initial set of query names. Each query name of the initial set of query names is associated with at least one document of the initial set of documents. The method also includes prioritizing the initial set of query names based on at least one topic label. The method also includes searching an additional set of documents to generate candidate query names. The method also includes prioritizing the candidate query names based on the at least one topic label. The method further includes applying a temporal search filter to each candidate query name to determine whether the candidate query name was processed within a time frame. The method further includes performing disambiguation processing on each candidate query name not processed within the time frame.

Abstract: Methods, apparatus, systems and articles of manufacture to perform identity matching across audience measurement systems are disclosed.

Abstract: A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the program aggregating data of an aggregation target table including at least one external tables relating to data other than data managed by the computer, includes executing processing of associating a specific item other than a date item as an aggregation unit of the external table having a plurality of items including the date item with an aggregate value list in which an aggregate value is stored in a unit of date item of predetermined granularity for each of the specific items on a one-to-one basis such that the aggregate value list of the specific item is specified by using the specific item as an index, and updating the aggregate value of the aggregate value list specified by using the specific item as the index when data stored in the external table is aggregated.

Abstract: Systems and methods are disclosed herein for identifying a category of a search term and providing search results subject to the identified category. These systems and methods may be performed by a media guidance application. The media guidance application may receive a search term that may correspond to different categories of items, and the media guidance application may identify a category that the search term is most likely related to using a hierarchical structure. The media guidance application may limit the search to the identified category of items.

Abstract: A computer system receives data identifying data fields used by sources of data and infrastructure information. The computer system maintains a storage state database to track information about the data fields. The computer system provides a graphical user interface through which a user can create, view, modify, and delete data defining classes and rules associated with classes. The computer system applies the rules to classify the data fields. The computer system provides a graphical user interface through which the classification of the data fields can be visualized in the context of infrastructure information for the sources of data.

Abstract: Techniques relating to managing “bad” or “imperfect” data being imported into a database system are described herein. A lifecycle technology solution helps receive data from a variety of different data sources of a variety of known and/or unknown formats, standardize it, fit it to a known taxonomy through model-assisted classification, store it to a database in a manner that is consistent with the taxonomy, and allow it to be queried for a variety of different usages. Auto-classification, enrichment, clustering model and model stacks, and/or other disclosed techniques, may be used in these and/or other regards.

Abstract: A method for performing multi-label classification includes extracting a feature vector from an input vector including input data by a feature extractor, determining, by a label predictor, a relevant vector including relevant labels having relevant scores based on the feature vector, updating a binary masking vector by masking pre-selected labels having been selected in previous label selections, applying the updated binary masking vector to the relevant vector such that the relevant label vector is updated to exclude the pre-selected labels from the relevant labels, and selecting a relevant label from the updated relevant label vector based on the relevant scores of the updated relevant label vector.

Abstract: The technology disclosed includes a system to perform multi-label support vector machine (SVM) classification of a document. The system creates document features representing frequencies or semantics of words in the document. Trained SVM classification parameters for a plurality of labels are applied to the document features for the document. The system determines positive and negative distances between SVM hyperplanes for the labels and the feature vector. Labels with positive distance to the feature vector are harvested. When the distribution of negative distances is characterized by a mean and standard deviation, the system further harvests the labels with a negative distance such that the harvested labels include the labels with a negative distance between the mean negative distance and zero and separated from the mean negative distance by a predetermined first number of standard deviations.

Abstract: Techniques for automatic extraction and verification of location data are disclosed. In some embodiments, a web crawler is configured to identify uniform resource locators (URLs), including a URL for a website associated with a target entity. The web crawler is further configured to fetch a subset of webpages from the website associated with the target entity. The web crawler may restrict the webpages that are fetched from the website based, at least in part, on patterns in the first website that are indicative of where reliable location information may be found. The web crawler further identifies a primary location of the target entity within at least one webpage in the subset of webpages, populating and/or verifying the primary location of the target entity in an entity profile. The entity profile may be consumed by client applications to execute location-aware and/or location dependent functions.

Abstract: An embodiment of a semiconductor package apparatus may include technology to create a range search tree based on a data stream, cluster data from the data stream based on the range search tree and application of a modified density based spatial cluster of applications with noise scheme, and detect an anomaly in the data stream based on the clustered data. Other embodiments are disclosed and claimed.

Abstract: Systems and methods for sequential detection-based classifications of radio-frequency identification (RFID) tags in three-dimensional space are provided. The methods include modeling a response from RFID tags as a probabilistic macro-channel and interrogating an RFID tag by transmitting a series of packets. Each packet is a transmit symbol and a first series of packet is a transmitted codeword. The method includes receiving, from the RFID tag, a second series of packets that is a received codeword in response to the transmitted codeword and finding a jointly typical transmit and receive codeword across all classes of macro-channels. The method also includes declaring a class of the RFID tag based on a largest likelihood between the transmitted codeword and the received codeword.

Abstract: Disclosed is a method of generating a multi-level summary of an article. The method may comprise generating, by a computing device, a low-level summary from article-matter in an article. The method may also comprise generating, by the computing device, a mid-level summary based on the low-level summary and the article-matter. The method may also comprise generating, by the computing device, an upper-level summary based on the mid-level summary, the low-level summary, and the article-matter.

Abstract: The present invention is a system and method of continuous sentiment tracking and the determination of optimized agent actions through the training of sentiment models and applying the sentiment models to new incoming interactions. The system receives conversations comprising incoming interactions and agent actions and determines customer sentiment on a micro-interaction level for each incoming interaction. Based on interaction types, the system correlates the determined sentiment with the agent action received prior to the sentiment determination to create and train sentiment models. Sentiment models include agent action recommendations for a desired sentiment outcome. Once trained, the sentiment models can be applied to new incoming interactions to provide CSRs with actions that will yield a desired sentiment outcome.

Abstract: Techniques for identifying clusters of user interactions and shopping missions may be provided. For example, the system may receive a history of interactions between a user and one or more network pages. The system may identify a most recent event from the history of interactions and identify a cluster that includes other events from the history of interactions that are of a same category as the most recent event. The determination of the cluster may be based in part on item attributes associated with the item presented on the at least one of the one or more network pages. The most recent event may then be associated with the cluster. In some examples, a shopping mission is determined and one or more notifications are provided to a user, merchant, or electronic marketplace in association with the identified shopping mission.

Abstract: A method of analyzing data is presented. The method includes receiving a query based for non-textual data, expanding search terms of the query, executing the query on one or more data sources, monitoring a specific data source selected from the one or more data sources. The monitoring is performed to monitor for matches to the query.

Abstract: A digital downloading jukebox system including a mechanism for delivering custom services to a recognized user is provided. For example, information specific to a recognized user may be stored and optionally may include a recognized user avatar representative of the recognized user. The user avatar may be an image, video, and/or animation, which may be displayed on and/or played through the jukebox. The user avatar may be associated with transactions associated with the user. For example, an avatar may be displayed when a playlist of the recognized user is played, when a message is sent, etc. In other examples, the avatar may introduce instances of media by playing an audio and/or video message, and the avatar may sing, dance, etc. while an instance of media is playing.

Abstract: Systems and methods are provided for tracking the provenance of donated genetic material using blockchain-based technologies. Immutable records of transactions associated with the donated genetic material are generated. These records can be utilized to create an audit trail for the genetic material.

Abstract: Disclosed is a similarity mining method, comprising: acquiring user behavior data and brand word data, wherein the user behavior data includes user search word data and user comment data; acquiring search brand words according to the user search word data and pre-stored brand word data; constructing a corpus important vocabulary library relating to the search brand words according to the user behavior data; using the corpus important vocabulary library as an input of a word vector tool to perform word vector model training to acquire word vectors of the search brand words; calculating a distance between the search brand words according to the word vectors of the search brand words. The invention further provides a similarity mining device, which calculates similarities of the brand words using a clustering algorithm (e.g., word2vector) according to the user search word data and the user post-purchase comment data.

Abstract: Techniques are disclosed for building a dictionary of words from combinations of symbols generated based on input data. A neuro-linguistic behavior recognition system includes a neuro-linguistic module that generates a linguistic model that describes data input from a source (e.g., video data, SCADA data, etc.). To generate words for the linguistic model, a lexical analyzer component in the neuro-linguistic module receives a stream of symbols, each symbol generated based on an ordered stream of normalized vectors generated from input data. The lexical analyzer component determines words from combinations of the symbols based on a hierarchical learning model having one or more levels. Each level indicates a length of the words to be identified at that level. Statistics are evaluated for the words identified at each level. The lexical analyzer component identifies one or more of the words having statistical significance.

Abstract: A computer-implemented method for analyzing calendar entries may include receiving, at a computing device, at least one calendar entry associated with a calendar application, the calendar entry comprising data defining a meeting type; tracking a user's activity in the meeting type; detecting at least one related calendar entry related with the received calendar entry, wherein the detected related calendar entry comprises a meeting type related to the meeting type of the received calendar entry; and supplementing the related calendar entry with at least one indicator describing the user's activity in the meeting type based on the tracked user activity.

Abstract: A method for recommending real-time information includes: obtaining user behavior data of a user; based on the user behavior data, respectively calculating a short-term interest, a long-term interest, and a real-time interest of the user; determining an interest of the user according to the short-term interest, the long-term interest, and the real-time interest of the user; and recommending real-time information to the user based on the interest of the user.