Skyline double-filtering retrieval method based on multi-medical factor in mobile O2O environment

A medical and environmental technology, applied in the field of database research, can solve problems that affect the final decision of users, and achieve the effect of improving fast user decision-making experience, high precision, and improving accuracy

CN106777095AInactive Publication Date: 2017-05-31DALIAN JIAOTONG UNIVERSITY
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
Publication Date
2017-05-31
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention provides a Skyline double-filtering retrieval method based on multi-medical factors in a mobile O2O environment, which aims to solve the problem that a conventional mobile network result set is too large. The technical key point is that the Skyline double-filtering retrieval method comprises the following step: on the basis of medical stream data and checking requests, extracting dimension sub-spaces of related medical attributes from the checking requests in parallel in a whole space by a cloud terminal, wherein d is a whole space dimension number, k is a sub-space data dimension number, and the field (dimension) in which a user is interested is extracted from the whole space F, namely k; and sequencing k-dimension sub-spaces according to preference degrees of a client terminal to the medical attributes, thereby obtaining a sequenced dimensional-grid index. The Skyline double-filtering retrieval method has the beneficial effects that feedback data can be continuously interacted and screened in a data stream mode, the precision is high and the method is applicable to big-data environments, accurate information which meets requirements can be provided by an interaction platform provided by users and data sections, and thus the accuracy of final decisions of the users and rapid user decision experience can be improved.
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Description

technical field

[0001] The invention belongs to the field of database research, and is a Skyline double-filter retrieval method based on multiple medical factors in a mobile O2O environment, involving large-scale data analysis, massive data processing in a mobile O2O environment, and medical intelligent data processing and application develop. Background technique

[0002] With the rapid development of the Internet, mobile O2O emerges as the times require, that is, the combination of offline business opportunities and the Internet makes the Internet the front desk for transactions. The improvement of people's living standards has made people pay more and more attention to health problems, and there are more and more medical searches. The explosive growth of massive data has made the traditional stand-alone data analysis and processing technology less and less suitable for the current intensive data analysis and processing needs. As an important variant algorithm of Skyline...

Examples

Embodiment 1

[0032] Embodiment 1: a Skyline dual-filter retrieval method based on multiple medical factors under a mobile O2O environment, comprising the following steps:

[0033] S1. Use the doctor terminal to collect real-time medical flow data in the O2O environment, and use the client terminal to initiate a query request. The query request includes multiple relevant medical attributes, the degree of preference for medical attributes, and the input threshold of each attribute;

[0034] S2. Based on the medical stream data and the query request, the cloud extracts the k (k≤d) dimensional subspace of the relevant medical attributes in the query request in parallel from the whole space, where d is the dimension of the whole space, and the data dimension of the k subspace, The fields (dimensions) that the user is interested in extracting from the full space F are both k. The k-dimensional subspaces are sorted according to the client's preference for each medical attribute to obtain an ordered...

Embodiment 2

[0046] Embodiment 2: A Skyline double-filtering retrieval method based on multiple medical factors in a mobile O2O environment. In order to solve the problems of high cost and huge result sets in processing massive data of multiple medical factors with the subspace Skyline algorithm in a mobile O2O environment, specific user needs Requirements, select representative points according to different user needs, mainly composed of three filtering methods A-filtering method, ε-filtering and D-filtering method, the execution steps are as follows:

[0047] S1. The mobile terminal combines the O2O environment and the establishment of a subspace Skyline query system with multiple medical factors, and uses the mobile terminal to collect real-time medical flow data and implement three filtering methods: A-filtering method, ε-filtering method and D-filtering method ;

[0048] S2. The intelligent mobile client adapts to the functional requirements and usage habits of different terminal medi...