A search apparatus (1) coupled to a database, the apparatus (1) comprising: a processor configured to execute instructions; a memory storing instructions which, when executed by the processor, cause the processor to: search the database for items containing a search term, wherein items containing the search term are matched items; identify fields corresponding to attributes of the matched items; define a range of values for each field; divide the range of values for each field into a plurality of ranged field buckets; distribute the matched items between the ranged field buckets based on attributes of the matched items that are within the range of values for each ranged field bucket; calculate an effectiveness value for each field based on the number of matched items in each of the ranged field buckets; select one or more top fields, each top field having an effectiveness value that is greater than a predetermined effectiveness value; and provide an effectiveness indicator output which is indicative of the effectiveness of each top field such that a user can use the effectiveness indicator output to select a top field for use as a filter in a further search.

A search apparatus (1) coupled to a database, the apparatus (1) comprising: a processor configured to execute instructions; a memory storing instructions which, when executed by the processor, cause the processor to: search the database for items containing a search term, wherein items containing the search term are matched items; identify fields corresponding to attributes of the matched items; define a range of values for each field; divide the range of values for each field into a plurality of ranged field buckets; distribute the matched items between the ranged field buckets based on attributes of the matched items that are within the range of values for each ranged field bucket; calculate an effectiveness value for each field based on the number of matched items in each of the ranged field buckets; select one or more top fields, each top field having an effectiveness value that is greater than a predetermined effectiveness value; and provide an effectiveness indicator output which is indicative of the effectiveness of each top field such that a user can use the effectiveness indicator output to select a top field for use as a filter in a further search.

A method of processing an information, an electronic device, and a storage medium are provided, which relate to a field of an artificial intelligence technology, in particular to a field of a knowledge graph technology. An implementation includes: determining a first information, in response to receiving a first query request; querying an information associated with the first information from a current graph database, so as to obtain a first query result; determining at least one federation node, according to at least one of the first query result and the first information; and sending a second query request to the at least one federation node, so that the at least one federation node queries an information associated with a second information in the second query request from a graph database corresponding to the at least one federation node, so as to obtain at least one second query result.

Exemplary embodiments of the present disclosure relate to systems, methods, and non-transitory computer-readable media for harvesting, parsing, and analyzing item identifiers in networked content to identify fraudulent content.

A method that predicts business income from user transaction data. A multinomial classifier is trained, using a vector of features from data related to a historical transaction and a label associated with the historical transaction, to generate a probability that the historical transaction belongs to a specific classification with respect to income. Data related to a new transaction is split into a set of unigrams. A new vector of features is generated from the data related to the new transaction. The new vector includes a set of values that correspond and are assigned to the set of unigrams. A classification with respect to income is determined for the new transaction by applying the multinomial classifier to the new vector. The new transaction is labeled with the classification. One or more fields of a form that is maintained by an online service is populated using the classification.

Techniques are described for responding to aggregate queries using optimizer statistics already available in the data dictionary of the database in which the database object targeting by the aggregate query resides, without the user creating any additional objects (e.g. materialized views) and without requiring the objects to be loaded into volatile memory in a columnar fashion. The user query is rewritten to produce a transformed query that targets the dictionary tables to form the aggregate result without scanning the user tables. “Accuracy indicators” may be maintained to indicate whether those statistics are accurate. Only accurate statistics are used to answer queries that require accurate answers. The accuracy check can be made during runtime, allowing the query plan of the transformed query to be used regardless of the accuracy of the statistics. For queries that request approximations, inaccurate statistics may be used so long as the statistics are “accurate enough”.

Presently disclosed are systems and methods for generating customized filtered-and-partitioned market-data feeds. In an embodiment, an output-feed profile is maintained in data storage at a market-data-processing device (MDPD). The output-feed profile specifies a subset of ticker symbols and a ticker-symbol-based feed-partitioning scheme. An input feed of order-book updates to ticker symbols is received at the MDPD from an upstream device. At the MDPD, a customized market-data output feed is generated according to the maintained output-feed profile at least in part by filtering the input feed down to the order-book updates to ticker symbols in the specified subset and partitioning the filtered feed according to the specified ticker-symbol-based feed-partitioning scheme. The customized market-data output feed is transmitted from the MDPD to a downstream device.

A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

A system for remote monitoring of an indicator of a device. The system includes a processor of an interpretation module connected to a sensor node and to a user device over a remote network; a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: query an admin database for new data acquired from the sensor node, search the admin database for a matching sensor ID, extract from the admin database recent entries corresponding to the sensor ID, determine if the entries indicate a pattern comprising at least one parameter, responsive to a detection of the pattern, search an interpretation database for a matching pattern comprising the parameter, extract interpretation data from an entry comprising the matching pattern, and provide the interpretation data to the user device.

A system for remote monitoring of an indicator of a device. The system includes a processor of an interpretation module connected to a sensor node and to a user device over a remote network; a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: query an admin database for new data acquired from the sensor node, search the admin database for a matching sensor ID, extract from the admin database recent entries corresponding to the sensor ID, determine if the entries indicate a pattern comprising at least one parameter, responsive to a detection of the pattern, search an interpretation database for a matching pattern comprising the parameter, extract interpretation data from an entry comprising the matching pattern, and provide the interpretation data to the user device.