Abstract: A message management method based on time and location is applied to the network system. Comprises obtaining a user account, a location information and a time information through an electronic device, and transferring the user account, the location information and the time information to a message server; obtaining a geographic information from a map database based on the location information, and displaying a region of the geographic information on a display of the electronic device; and in a display page of the display, using the user account, the time information and the region as a filter condition, obtaining a name, an avatar of a relevant user from a user database, and obtaining a message of the relevant user from a message database, and displaying the name, avatar and message of the relevant user on the display page according to the sending location of the message.

Abstract: A system and method for clustering computing interface calls. A method includes: determining a plurality of computing interface cluster definitions, the plurality of computing interface cluster definitions including a plurality of parameter type strings; and clustering a plurality of computing interface call instances into a plurality of clusters based on the plurality of computing interface cluster definitions, wherein a number of clusters among the plurality of clusters is fewer than a number of computing interface call instances among the plurality of computing interface call instances, wherein clustering the plurality of computing interface call instances includes determining a plurality of portions of the plurality of computing interface call instances which match types of parameters represented by respective parameter type strings of the plurality of parameter type strings.

Abstract: User interfaces for presenting media items are described. In one example, an electronic device receives a user input specifying a hashtag in a first user interface of an application of an electronic device, and in response, provides, for display, a second user interface that comprises a first portion, a second portion, and a third portion, wherein: the first portion is configured to receive a sequence of text, and the sequence of text comprises the hashtag by default; the second portion comprises a search result based on the hashtag, the search result comprises a plurality of media items associated with the hashtag; and the third portion is configured to receive one or more user interactions for creating a new media item.

Abstract: An automotive data processing system includes a storage subsystem and a processor. The storage subsystem is disposed in a vehicle and is configured to store at least data produced by one or more data sources of the vehicle. The processor is installed in a vehicle and is configured to apply, to the data stored in the storage subsystem or that is en route to be stored in the storage subsystem, at least one model that identifies one or more specified features-of-interest in the data, so as to generate metadata that tags occurrences of the specified features-of-interest in the stored data, and to export at least part of the metadata to an external system that is external to the vehicle.

Abstract: A method and a computer program for discovering possible errors in a production process for manufacturing metal products. The method involves removing at least one process parameter value from the cluster or adding at least one process parameter to the cluster. Second Z-score values, which are compared with the first Z-score values, are then determined for the thus-altered cluster. The changes in the Z-score values provide suggestions for troubleshooting and process optimization which are direct and can be implemented immediately.

Abstract: Data races are resolved and rows are deduplicated between upqueries and updates to an underlying database, in a database caching layer on top of the underlying database. The caching layer maintains a dataflow graph of nodes representing row data of the underlying database, database operators, and partially or fully materialized queries, wherein queries that use common row data and/or database operators share corresponding nodes. A data race resolution and row deduplication algorithm may be applied on every node that contains a partial materialization, and is correct regardless of how many times this node is reused throughout the dataflow graph. It prevents any of the nodes from seeing duplicated packets between the external upqueries that are originated from each node and any underlying database change events which the node observes.

Abstract: An apparatus for conditioning raw data based on temporal interpolations to generate optimal extrapolations of an entity, comprising a processor and a memory containing instructions configuring the processor to receive raw data associated with a temporal element from an entity condition the raw data, wherein conditioning the raw data includes clustering the raw data into primary clusters, wherein clustering the raw data includes dividing each primary cluster into a plurality of secondary clusters each contains a corresponding temporal interpolation, and ranking the plurality of secondary clusters as a function of the corresponding temporal interpolations, determine an extrapolation for each secondary clusters of the ranked plurality of secondary clusters based on the conditioned raw data, and generate a progression model as a function of the extrapolations.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses for generating synthetic data based on time series predictions and plural machine learning models. Generating the synthetic data may include receiving one or more data records that include transaction data of a user, categorizing and/or segmenting the one or more data records, determining a first predicted time step based on the categorizing and/or segmenting, and performing an iterative process that determines further predicted time steps. The first predicted time step may be determined using one model of a plurality of machine learning models. The iterative process may determine the further predicted time steps using the plural machine learning models. Based on iterations of the iterative process, potential time series may be determined. The synthetic time series may be determined from the potential time series. The synthetic time series may be used by additional processes, such as additional machine-learning processes.

Abstract: Processes and machines are disclosed for detecting malicious email campaigns based on unique but similarly spelled attachments. Email log(s) from network appliances are retrieved, filtered, normalized, and converted into field-based organized data for comprehensive analysis. Cluster analysis is performed. Filenames of email attachments are transformed into numerical vectors and a cosine similarity termset analysis is performed on the numerical vectors. Data is organized into time bins for burst detection. Statistical analysis is performed on the time bins. Pattern recognition is performed to identify alphanumeric similarities in the filenames of the attached files in order to detect malicious email campaigns. Machine learning may be used to optimize the cosine similarity threshold and other query variables, and to update existing cybersecurity filters and firewalls. Mitigation can be performed to remove malicious emails that were delivered to recipient mailboxes.

Abstract: The present invention proposes a method for intelligent management of valve production process data, a medium, and an apparatus. Through results of grid classification of sampling points, the method constructs information entropy of grid distribution density levels as well as grid distribution density, which takes into account the circumstance that sampling points may not exist in the classification space, so as to avoid grids where sampling points do not exist from affecting the local density of the sampling points; secondly, based on the core relative distance of the sampling points in a seed grid, the method constructs a coverage density distance, which takes into account the magnitude of the local density of the sampling points in the seed grid as well as differences in the distance from sampling points that have a relatively large local density in the other seed grids.

Abstract: An example operation may include one or more of receiving, by a resolver node, asset data to be recorded on a blockchain, executing, by the resolver node, a smart contract to apply an asset data validation format to the asset data, rejecting, by the resolver node, non-conforming asset data from being stored on the blockchain based on the execution of the smart contract, and accepting the asset data validated by the smart contract.

Abstract: Low latency search for nearest neighbors in a dataset containing a large number of entries is improved using an error correction code (ECC) for partitioning data into clusters and retrieval. During initialization and preprocessing a d-dimensional space with clusters corresponding to ECC codewords is specified. Entries in the dataset are embedded into this space and associated with respective codewords, each codeword specifying a cluster. An index associates the codewords, clusters, and entries. During a query of the dataset, a query entry is processed to determine a query embedding in the d-dimensional space. The query embedding is used as input for a list decoder of the ECC. The list decoder provides a set of nearest codewords, with those codewords representing a set of candidate clusters that may contain nearest neighbors. The dataset entries associated with the candidate clusters may then be searched to determine query results comprising specific entries.

Abstract: Techniques and a system to facilitate estimation of a quantum phase, and more specifically, to facilitate estimation of an expectation value of a quantum state, by utilizing a hybrid of quantum and classical methods are provided. In one example, a system is provided. The system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can include an encoding component and a learning component. The encoding component can encode an expectation value associated with a quantum state. The learning component can utilize stochastic inference to determine the expectation value based on an uncollapsed eigenvalue pair.

Abstract: According to the present invention, provided is a method for collecting filtered text data, comprising the steps in which: a computing device acquires first text data and records the first text data in a text data pool; the computing device acquires second text data; the computing device performs a calculation in a deep learning model by using the first text data and the second text data as input values and calculates a first feature vector corresponding to the first text data and a second feature vector corresponding to the second text data; and the computing device compares the degree of similarity between the first feature vector and the second feature vector, and records the second text data in the text data pool when the degree of similarity is less than a predetermined value.

Abstract: A risk-prediction-preparation module to generate a risk-prediction-model, is provided herein. The risk-prediction-preparation module includes accessing a data-storage of transactions to operate a group-by operation on transactions related to data-points, according to a logical-entity into entities. Then, clustering entities of a clean-financial dataset into clusters. Selecting data-points of: (a) entities from the clusters to a first dataset and (b) a preconfigured amount of entities randomly to a second dataset. Selecting all entities that have at least one ‘fraudulent’ data-points in at least one related data-point to add all the entities to the first dataset and the second dataset. Using vectorized and scaled extracted features for training a first machine-learning-model of fraud detection on the first dataset and training a second machine-learning-model of fraud detection on the second dataset to collect results.

Abstract: A method including generating, by a navigation service, a route for navigating from a route origin to a route destination using a private roads repository. The method includes identifying a ghost origin and a ghost destination of a ghost road along the route. The method includes sending, using an application programming interface of a base roads engine, a first request for a route from the ghost origin to the ghost destination. The method includes receiving, from the base roads engine in response to the first request, a replacement section from the ghost origin to the ghost destination. The method includes replacing, in the route, the ghost road with the replacement section to create an updated route including segments. The method includes generating an estimated travel time from the route origin to the route destination over the segments of the updated route. The method includes presenting the estimated travel time.

Abstract: A method for deployment of machine-learning based operators within a query is described. For this embodiment, a sequence of operators associated with a query is identified, which includes at least a first operator and at least a second operator. The second operator is configured to perform operations, in accordance with a machine learning (ML) component, on data received as input from execution of the first operator. Schemas associated with the machine learning component is retrieved along with schemas associated with other operators within the sequence. Compatibility between at least an output schema associated with the first operator and an input schema associated with the second operator associated with the ML component is determined. Thereafter, a portion of the sequence of operators including at least the second operator and another operator of the sequence of operators successive to the second operator may be stored within a data store for subsequent use.

Abstract: A system and method of enhancing the trustworthiness of an artificial intelligence system include detecting whether a data element includes an existing data domain tag, processing the data element into a transformed data element, generating a data domain tag, where the data domain tag includes at least a data domain identifier and a timestamp, appending the data domain tag to the transformed data element, creating a signature for the transformed data element and the appended data domain tag using a private key, and creating another signature for the data domain tag using the private key.

Abstract: A system for automated information support processing is disclosed. The system may receive a natural language information support request from a plain text input channel. The system may determine a first user intent based on the information support request. The system may compare the first user intent with a set of support rules. The system may determine a dispositioned outcome based on the set of support rules and the user intent. The system may return the dispositioned outcome.

Abstract: An example system includes a processor to execute a key point analysis to extract key points from a number of input sentences. The processor can compute directional relation scores between the extracted key points. The processor can construct a key point graph based on the extracted key points and the directional relation scores. The processor can generate a key point graph visualization based on the key point graph.

Abstract: A method and apparatus for preparing an image on a cloud platform, and a device and a storage medium are provided. The method may include: receiving an image request for a target object, and obtaining a first storage backend of the target object according to the image request; obtaining a second storage backend of a Glance service in the cloud platform, and comparing the second storage backend with the first storage backend; and obtaining an image for the target object on the second storage backend in a cloning manner when the first storage backend is the same as the second storage backend. According to the method, when the first storage backend is the same as the second storage backend, the image for the target object is obtained on the second storage backend in the cloning manner, so that the downloading and uploading processes are omitted.

Abstract: Existing content such as books are reorganized and condensed as electronic books for display on a mobile computing device. The electronic books have a hierarchical structure. A user interacts with the content of the book by way of a touch screen of the mobile computing device. The navigation may be non-linear in nature and the book is reconstructed as a set of primary ideas, supporting ideas, stacks of cards for the supporting ideas, and individual cards comprising elements and commentary from or about the book.

Abstract: Domain name system (DNS) configuration during virtual private network (VPN) connection includes, by a VPN entry server, receiving from a client device, via a VPN tunnel between the entry server and the client device, a first request for first content that identifies a first external source for the first content, receiving, from an operative DNS server configured for the tunnel, an Internet Protocol (IP) address of a first VPN system exit server, in response to determining that the first content is unavailable via the first system exit server, identifying a second DNS server, such that a second VPN system exit server for obtaining the first content is available using the second DNS server, obtaining, from the second system exit server, the first content, wherein the second system exit server obtained the first content from the first external source, and transmitting, to the client device, via the tunnel, the first content.

Abstract: Embodiments disclosed herein describe systems and methods to generate statuses of higher level integrated logical clusters from one or more output files generated by the clusterwares of a plurality of lower level physical clusters. The systems and methods provide an interactive dashboard graphical user interface (GUI) rendering the statuses of the higher level logical clusters. In response to a drill down selection by the system administrator, the systems and methods may render resource level statuses of the plurality of resources forming the higher level logical cluster. Therefore, by using a single dashboard, a system administrator can seamlessly transition between statuses at different level of abstractions for multiple resources distributed across multiple geographically diverse datacenters. Furthermore, the dashboard allows the system administrator to perform failover operations.

Abstract: Provided are a computer program product, system, and method for pre-processing a table in a document for natural language processing (NLP). A graphical user interface (GUI) provides a representation of table items in a table in a document including a set of a main element comprising an entity whose value is to be extracted, a conditional element that refines the entity, and a value element comprising a value for the entity. Graphical controls are rendered in the GUI to enable a user to select an element from the table to be the main element, conditional element, and value element. The set of the main element, conditional element, and value element are updated with the user selected element to form a modified set. The modified set of the main element, conditional element, and the value element are provided to an NLP engine to perform natural language processing.

Abstract: The present disclosure relates to database technology and in particular to dynamically updating and customizing database partitions. A computer-implemented engine is disclosed for identifying and retrieving a number of data records applicable to generate a response to a request, the engine having access to at least two partitions. Partition statistics are generated indicating correlations between the data records and, based on that partition statistics, the data records having the strongest correlation with each other are relocated to partitions so that the number of partitions which have to be queried in order to generate a response to a data request is minimized. Furthermore, the computational load caused when generating responses is more equally distributed across the partitions.

Abstract: A system for generating a workload model for a target information handling system includes gathering workload data from a plurality of information handling systems, dividing the workload data into a plurality of workload data bins, identifying workload data characteristics for each workload data bin and identifying workload data sets that may be applicable to the target information handling system. A workload mix may be determined based on the target information handling systems and workload data characteristics. Real customer workload data including real-time or near real-time workload data may be used to check a workload model for accuracy before deploying the workload model to a target information handling system.

Abstract: Embodiments of the present disclosure relate to an article processing method, electronic device, and computer program product. The method includes: determining, based on content of a target article, a target article vector associated with the target article; acquiring a reference article vector set associated with a reference article set; and determining, based on a distance in an article vector space between the target article vector and a reference article vector in the reference article vector set, a reference article vector associated with the target article vector in the reference article vector set as an association article vector. By using the technical solution of the present disclosure, an association article associated with a target article can be accurately provided based on the target article selected by a user, so that reports on the target article and its association articles can be further provided to the user for analysis and selection.

Abstract: Methods, systems, and computer-readable media are disclosed herein to provide rule-based reconciliation of records. Specifically, rules are utilized to reconcile one or more records and identify duplicates therein. Once duplicate records are identified, one or more ranking sets can be utilized to identify which of the duplicate records to write to the system.

Abstract: Clustering structured log data by key-values includes receiving, via a user interface, a request to apply an operator to cluster log messages according to values for keys associated with the request. At least a portion of each log message comprises structured machine data including a set of key-value pairs. The method further includes receiving a log message and determining whether to include the log message in a cluster based at least in part on an evaluation of values in the structured machine data of the log message for the keys associated with the request. The cluster is included in a set of clusters. Each cluster in the set is associated with a different combination of values for the keys associated with the request. The method further includes providing, via the user interface, information associated with the cluster.

Abstract: Systems and methods for scaling application and/or storage system functions of a distributed storage system based on a heterogeneous resource pool are provided. According to one embodiment, the distributed storage system has a composable, service-based architecture that provides scalability, resiliency, and load balancing. The distributed storage system includes a cluster of nodes each potentially having differing capabilities in terms of processing, memory, and/or storage. The distributed storage system takes advantage of different types of nodes by selectively instating appropriate services (e.g., file and volume services and/or block and storage management services) on the nodes based on their respective capabilities. Furthermore, disaggregation of these services, facilitated by interposing a frictionless layer (e.g.

Abstract: A storage device generates and stores a key stream and a value stream by extracting from data a plurality of keys and a plurality of values respectively corresponding to the plurality of keys. The storage device includes a controller and a non-volatile memory. The controller receives from a host information about an invalid key included in the key stream together with a compaction command, and performs a compaction operation on the key stream in response to the compaction command. The non-volatile memory stores the key stream and the value stream. The controller merges the key stream with another key stream based on the information about the invalid key in the compaction operation.

Abstract: Embodiments of the present disclosure provide for improved determination of complexities associated with event data objects. Such complexity determinations may be identified based at least in part on complexity score(s) generated from any number of augmented event codes. Embodiments identify augmented event codes from any of a myriad of sources, including various service encodings and participant history profiles for particular event entities. The augmented event codes may be processed in a myriad of ways, utilizing the entirety and/or portions thereof, to further enhance the accuracy of the event complexity determined therefrom. Based at least in part on the accurately generated complexity determination(s), one or more prediction-based actions may be initiated that correspond to the particular complexity determination(s), for example such that only the correct prediction-based action is initiated based at least in part on such a determined event complexity.

Abstract: A computer system displays a coalesced representation of a plurality of notifications in a notification-display user interface, wherein the coalesced representation, when selected, causes the computer system to concurrently display individual representations of at least two of the plurality of notifications in the notification-display user interface.

Abstract: A wearable electronic device may include a display, a camera, at least one first sensor, and at least one processor operatively coupled to the display, the camera, and the at least one first sensor.

Abstract: A data intake and query system can generate local data enrichment objects and receive federated data enrichment objects from another data intake and query system. In response to receiving a query, the data intake and query system can determine whether the query is subquery of a federated query. If the query is a subquery, the data intake and query system can use the federated data enrichment objects to execute the query.

Abstract: Based on a predetermined number of available processor sockets, a plurality of candidate matrix decompositions are identified, which correspond to a multiplication of matrices. Based on a first comparative relationship of a variation of first sizes of the plurality of candidate matrix decompositions along a first dimension and a second comparative relationship of a variation of second sizes of the plurality of candidate matrix decomposition sizes along a second dimension, a given candidate matrix decomposition is selected. Processing of the multiplication among the processor sockets is distributed based on the given candidate matrix decomposition.

Abstract: Systems and methods are provided for receiving a time series dataset from a monitored processor and group the dataset into a plurality of clusters. Using an unsupervised machine learning model, the system may combine a subset of the plurality of clusters by data signature similarities to form a plurality of motifs and combine the plurality of motifs into one or more shapelets. In some examples, the system may train a supervised machine learning model using the plurality of motifs and the one or more shapelets as input to the supervised machine learning model. The system can perform various actions in response to labelling the time series dataset, including predicting a second time series dataset, determining that a monitored processor corresponds with an overutilization at a particular time, or suggesting a reduction of additional utilization of the monitored processor.

Abstract: A processor may receive a video including a plurality of video frames in sequence and a question regarding the video. For a video frame in the plurality of video frames, a processor may parse the video frame into objects and relationships between the objects, and create a subgraph of nodes representing objects and edges representing the relationships, where parsing and creating are performed for each video frame in the plurality of video frames, where a plurality of subgraphs can be created. A processor may create a hypergraph connecting subgraphs by learning relationships between the nodes of the subgraphs, where a hyper-edge is created to represent a relationship between at least one node of one subgraph and at least one node of another subgraph in the plurality of subgraphs. A processor may generate an answer to the question based on the hypergraph.

Abstract: Disclosed is an autonomous mining method of industrial big data based on model sets, which comprises the following steps: S1, building model sets and a mining engine based on domain knowledge and structural characteristics of multi-source heterogeneous data; S2, carrying out data sampling on the multi-source heterogeneous data, and counting the fault-tolerant estimation of random error variance; S3, mining data sets by using the mining engine, and determining the optimal fault-tolerant model of each sampled data sequence and the optimal fault-tolerant estimation of model parameters; S4, performing goodness-of-fit statistics calculation and VV&A test by using the optimal fault-tolerant model; S5, acquiring data model representation and connotation knowledge based on model clustering. The method can realize the automation of the mining process of big data, the integration of associated knowledge, the expansion of model sets, the integration of mining and modeling and the optimization of mining results.

Abstract: Records can be matched by a graph neural network model performing entity resolution on the records, and representing each record as a respective node in a graph. Record matching explanations can be generated, each record matching explanation indicating a first set of attributes, and a first set of corresponding values, used for the matching at least two of the records. Nodes can be clustered into a plurality of clusters by aggregating the record matching explanations and, based on the record matching explanations, determining which of the records have high importance values, in the first set of values, that match. At least one cluster explanation can be generated, the cluster explanation indicating a second set of attributes, and a second set of values corresponding to the second set of attributes, used for the clustering the nodes. The record matching explanation and the cluster explanation can be output.

Abstract: Some embodiments provide a program that determines a plurality of data objects. Each data object in the plurality of data objects includes a first attribute and a second attribute. The program further sorts values of the first attribute of the plurality of data objects. The program also sorts values of the second attribute of the plurality of data objects. The program further determines a first distance value based on the sorted values of the first attribute of the plurality of data objects. The program also determines a second distance value based on the sorted values of the second attribute of the plurality of data objects. The program further defines a plurality of clusters based on the sorted values of the first attribute of the plurality of data objects, the first distance value, the sorted values of the second attribute of the plurality of data objects, and the second distance value.

Abstract: Accordingly, embodiments herein disclose a method and apparatus for retrieving intelligent information from an electronic device (100). The method includes receiving, by the electronic device (100), an input from a user. Further, the method includes identifying, by the electronic device (100), at least one data item to generate at least one metadata tag. Further, the method includes automatically generating, by the electronic device (100), the at least one metadata tag related to the at least one data item based on a plurality of parameters. Further, the method includes providing, by the electronic device (100), at least one priority to the at least one metadata tag. Further, the method includes storing, by the electronic device (100), the at least one metadata tag at the electronic device (100).

Abstract: Domain Name System (DNS) security using process information is provided. An application accessing an internet service using a domain name is determined. Process information associated with the application along with an associated DNS query to identify an IP address associated with the domain name are identified. The process information and the associated DNS query to a DNS security service are sent. An action based on a response from the DNS security service is performed.

Abstract: A computer implemented method includes building a Positive Knowledge Base with directive words, designated verbs and designated objects. A Negative Knowledge Base with designated phrases and designated legal terms is built. Tasks and phrases from the Positive Knowledge Base and the Negative Knowledge Base are built. Regulations are received. Phrases from the regulations are weighted against the Positive Knowledge Base and the Negative Knowledge Base to isolate positive Maintenance Compliances. The positive Maintenance Compliances are matched to tasks to derive ranked Maintenance Compliances. The ranked Maintenance Compliances are supplied.

Abstract: An imaging mass spectrometry unit (1) executes predetermined analysis on each of a plurality of micro areas set in a two-dimensional measurement region on a sample or a three-dimensional measurement region in a sample to acquire spectrum data. A clustering execution section (21) classifies spectrum data for a plurality of measurement points obtained for a reference sample into any of a plurality of clusters. A clustering model information storage section (22) stores a clustering model obtained by clustering processing. A segmentation execution section (23) classifies respective spectral data for a plurality of measurement points obtained for a sample other than a reference sample using a clustering model, and a spatial distribution image creation section (24) creates a segmentation image obtained by partitioning a two-dimensional or three-dimensional image into a plurality of small regions on the basis of a result of the classification.

Abstract: Messages, such as text messages, emails, and social media posts, are a popular way to communicate, however, messages can be overwhelming. In order to better manage messages, messages may be grouped, such as those having a common topic. A recipient may then address the grouped messages as a group. However, certain messages may have a common topic but have an attribute that warrants maintaining the message as individual messages, excluded from the group. For example, the message may be from someone who rarely communicates with the recipient, a celebrity, an important figure at work or in politics, a family member, or other attribute that would warrant exclusion from a common topic group.

Abstract: A computer-implemented method, comprising: using a normalization service of a first application virtual compute instance hosted in and executing in a cloud computing facility, accessing a plurality of digitally stored data records of a transaction processing system, each of the data records comprising a plurality of data values for a corresponding plurality of attributes; using the normalization service, executing a data cleaning operation on the data records by programmatically calling two or more data cleaning functions, each of the data cleaning functions corresponding to a particular attribute among the plurality of attributes; using the normalization service, creating and storing a plurality of clusters in memory of the first application virtual compute instance by clustering the data records based on exact matches of the data values of a first attribute and creating and storing references to the data records in the clusters; using the normalization service, joining two or more clusters among the plurali

Abstract: Methods, systems, and computer programs are presented for displaying a customized news stream. One method includes an operation for identifying dwell times spent by users while accessing a first plurality of items, each item belonging to one media type from a plurality of media types (e.g., news articles, videos, slide shows, etc.). In addition, the method includes operations for determining statistical parameters for each media type based on the identified dwell times, and for detecting a news corpus having a second plurality of items. A priority for each item in the news corpus is determined based on the media type of the item, the corresponding statistical parameters for the media type of the item, and the profile of a user. The news stream is sent to the user for presentation on a display, the news stream being sorted based on the priority of the items in the news corpus.

Abstract: Methods, systems, and media for lot classification are disclosed. In one example, a classification system for identifying lot listings receives a description for a listing in a publication system, identifies a string in the listing, identifies a quantity word or digit in the string, and converts an identified quantity word into digit form. A normalized string is tokenized to produce tokens, the tokenizing of the normalized string including splitting the normalized string into a series of substrings using a sequence of delimiters. For each substring, an additional split is performed by separating any digit from any other adjacent character, unless that character is another digit, and maintaining an internal character order of each split substring to produce a flattened list of tokenized tokens.