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Priority query algorithm and system based on location top-k keyword query under sliding window

A top-k, sliding window technology, applied in the computer field, can solve the problem of no update rate of the system, and achieve the effect of improving query speed, good performance, and avoiding calculation

Active Publication Date: 2020-08-11
SHENZHEN UNIV
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  • Application Information

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Problems solved by technology

However, neither system has a good update rate

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  • Priority query algorithm and system based on location top-k keyword query under sliding window
  • Priority query algorithm and system based on location top-k keyword query under sliding window
  • Priority query algorithm and system based on location top-k keyword query under sliding window

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Embodiment Construction

[0062] The present invention is described in further detail now in conjunction with accompanying drawing. These drawings are all simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, so they only show the configurations related to the present invention.

[0063] 1. Problem definition

[0064] Let D be a two-dimensional Euclidean space, W be a sliding window, and S be a collection of geographic text information in D and W. Each geographic text information is expressed as o=(pos, text), where pos is a position point in D, and text is text information. A LkTQ q consists of a tuple (loc,k), where loc represents the query location point, and k represents the number of result keywords that can be specified by the user. Finally, k keywords with the highest position-aware word frequency scores in the information in W are returned.

[0065] The position-aware word frequency score of a word t in a sliding window W is ...

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Abstract

A position top-k keyword query-based priority query algorithm and system under a sliding window. The algorithm comprises the following steps: step 1, inputting a constructed quadtree indexing model, a query node and k, and initializing a set of results; step 2, executing a branch trim operation to obtain a set of candidate results; step 3, using a maximum heap C to store each word in the set of candidate results and the score thereof; step 4, when the size of the set of results is smaller than k, sequentially taking a word at a queue head from C, traversing from a root node to a leaf node to find the accurate score thereof and placing same into a queue; step 5, cyclically carrying out step 4, and when the score of the word at the queue head is equal to the accurate score of the word in the leaf node, placing same in the set of results; and step 6, when the size of the set of results is equal to k, returning the set of results. The algorithm and system can effectively trim a search space according to word frequency and position proximity, and avoids unnecessary computations while ensuring that no candidate word is lost, greatly reducing computation costs and improving the speed of querying.

Description

technical field [0001] The invention belongs to the field of computers, and in particular relates to a query algorithm, in particular to a priority query algorithm suitable for querying based on position top-k keywords under a sliding window. In addition, the invention also relates to a priority query system based on position top-k keyword query under a sliding window. Background technique [0002] With the proliferation of social media, cloud storage and location-based services, the number of messages containing text and geographic information (for example, geotagged tweets) has soared. Such news, which can be modeled as geotext data streams, can often provide first-hand information for a variety of local events of different types and sizes, including news stories in a region, urban disasters, local business promotions, and events of public concern in the city. hot topics etc. [0003] The data streams of location-based social media have the following properties: (1) Burs...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/31G06F16/332
CPCG06F16/319G06F16/322G06F16/3323
Inventor 毛睿李荣华陆敏华王毅罗秋明商烁刘刚
Owner SHENZHEN UNIV
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