Abstract:
Techniques related to approximate nearest neighbor searching are discussed. Such techniques may include traversing an approximate nearest neighbor search tree from root node to a resultant leaf node while maintaining a priority queue of best matches, determining candidate entries for evaluation based on the resultant leaf node, and generating search results based on the priority queue and the candidate entries.
Abstract:
A panelist identification device for determining an identity of a panelist based on an input interaction pattern of the panelist is provided. Additionally, a method for determining an identity of a panelist based on an input interaction pattern of the panelist is provided. Further, a computer-readable storage device having processor-executable instructions embodied thereon is provided. The instructions are for determining an identity of a panelist based on an input interaction pattern of the panelist.
Abstract:
Described are methods, systems, and computer program products for correlating operational information with subsequent action information. Operational information is received from a computing system performing one or more services. Pattern matching is performed for the operational information with data within a knowledge base. Based on the results of the pattern matching, a subsequent action associated with the operational information is determined.
Abstract:
Aspects of the technology described herein provide a personalized computing experience for a user based on a predicted future semantic location of the user. In particular, a likely future location (or sequences of future locations) for a user may be determined, including contextual information about the future location. Using information from the current context of the user's current location with historical observations about the user and expected user events, out-of-routine events, or other lasting or ephemeral information, a prediction of one or more future semantic locations and corresponding confidences may be determined and used for providing personalized computing services to the user. The prediction may be provided to an application or service such as a personal assistant service associated with the user, or may be provided as an API to facilitate consumption of the prediction information by an application or service.
Abstract:
Изобретение относится к области контрольно-вычислительной техники. Предложен способ построения маршрута логического вывода в базе знаний, содержащей представление модели предметной области в виде объектов и связей, организованных в ориентированный биграф. Объекты содержат параметры, а связи содержат правила, каждое правило имеет входную переменную и выходную переменную, а каждый связанный с правилом параметр является либо его входной переменной, либо выходной переменной. Формируют совокупность известных параметров и задают один или более искомых параметров. В способе выполняют обработку для каждого известного параметра, ранее не проходившего данную обработку, в целях нахождения искомых параметров. Обработка содержит этапы: определяют запускаемые правила, в которых известный параметр является входной переменной, для которых известны все остальные входные переменные и которые не запускались раньше, запускают эти определенные запускаемые правила и дополняют совокупность известных параметров выходными переменными запущенных правил, если найдены все искомые параметры, обработку прекращают. Строят последовательность из запущенных правил в порядке их запуска, которая представляет маршрут логического вывода.
Abstract:
The present invention relates to a method for crowd detection in an area, wherein moving patterns of persons in the area and the number of persons within and/or moving from and/or to the area over a certain time period are determined to obtain model training data sets, wherein said model training data sets are each assigned to represent one of one or more predefined crowd levels in the area, wherein a crowd detection model is generated based on the model training data sets, and wherein an actual crowd level for the area is estimated using the generated crowd detection model with actual data of moving profiles and/or the actual number of persons within and/or moving from and/or to the area over a certain time period. The present invention further relates to a system for crowd detection in an area.
Abstract:
A computer implemented method for generating a pattern matching machine for identifying matches of a plurality of symbol patterns in a sequence of input symbols, the method comprising: providing a state machine of states and directed transitions between states corresponding to the plurality of patterns; applying an Aho-Corasick approach to identify one or more mappings between states in the event of a failure, of the state machine in a state and for an input symbol, to transition to a subsequent state based on the directed transitions of the state machine, characterised in that one of the symbol patterns includes a wildcard symbol, and a mapping for a state representing pattern symbols including the wildcard symbol is provided in a hash table referenced based on a key, the key being based on a unique identifier of the state and the input symbol to be received, by the pattern matching machine in use, to constitute the wildcard symbol.
Abstract:
Disclosed are methods and devices, among which is a device that includes a finite state machine lattice (30). The lattice (30) may include a counter (58) suitable for counting a number of times a programmable element (34, 36) in the lattice (30) detects a condition. The counter (58) may be configured to output in response to counting the condition was detected a certain number of times. For example, the counter (58) may be configured to output in response to determining a condition was detected at least (or no more than) the certain number of times, determining the condition was detected exactly the certain number of times, or determining the condition was detected within a certain range of times. The counter (58) may be coupled to other counters (58) in the device for determining high-count operations and/or certain quantifiers.
Abstract:
The described method and system assist an interpreter in analyzing seismic (702), geophysical, or geoscience data. In particular, the method and system includes defining a conceptual model (712) of subsurface hydrocarbon accumulations; defining an interpretational model (710) linking observations to concepts; obtaining and entering observations into a database; querying the database (714) for instances of particular concepts or classifying observations with regard to different concepts; and repetition of the above steps for additional iterations.
Abstract:
A method and system that includes extracting event models from at least one personal planning source of a user, wherein a parameter of an event model includes event location; periodically receiving location information of at least one mobile device of the user; storing the location information in a location log; a pattern worker module maintaining user location patterns through the location log; generating a location prediction from the extracted event models and the user location patterns; a first content worker module checking if the location prediction meets a set of content requirements; if the set of content requirements is satisfied, initiating content retrieval from at least one service; and pushing the content to the mobile device.