WO2017054330A1 - 资源组合处理方法、装置、设备及计算机存储介质 - Google Patents

资源组合处理方法、装置、设备及计算机存储介质 Download PDF

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WO2017054330A1
WO2017054330A1 PCT/CN2015/098084 CN2015098084W WO2017054330A1 WO 2017054330 A1 WO2017054330 A1 WO 2017054330A1 CN 2015098084 W CN2015098084 W CN 2015098084W WO 2017054330 A1 WO2017054330 A1 WO 2017054330A1
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network resource
search
value
heat level
resource combination
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PCT/CN2015/098084
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English (en)
French (fr)
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杨兴
杨晓静
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百度在线网络技术（北京）有限公司
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Priority to JP2016567091A priority Critical patent/JP6303231B2/ja
Priority to US15/313,552 priority patent/US10521437B2/en
Priority to EP15892066.0A priority patent/EP3358473A4/en
Priority to KR1020167031107A priority patent/KR101868729B1/ko
Publication of WO2017054330A1 publication Critical patent/WO2017054330A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/06—Asset management; Financial planning or analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G06F16/24578—Query processing with adaptation to user needs using ranking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/285—Clustering or classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/951—Indexing; Web crawling techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/12—Discovery or management of network topologies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications

Definitions

  • the present invention relates to the field of Internet technologies, and in particular, to a resource combination processing method, apparatus, device, and computer storage medium.
  • the combination of network resources may have more beneficial effects.
  • the combination of the user's location resource and the demand resource can push the user to more information that meets the user's needs, which is beneficial to improving the accuracy of the information push.
  • the combination of purchasing a variety of wealth management products can reduce investment risks and help to improve investment returns.
  • the network resource combination may bring different beneficial effects, which means that the combination of network resources is not static, and the network resource combination needs to be constantly adjusted. However, how to determine whether you need to adjust the network resource combination is the primary problem.
  • aspects of the present invention provide a resource combination processing method and apparatus for determining whether a network resource combination needs to be adjusted, so as to facilitate timely adjustment of a network resource combination.
  • An aspect of the present invention provides a resource combination processing method, including:
  • Another aspect of the present invention provides a resource combination processing apparatus, including:
  • An obtaining module configured to acquire, according to search volume data of each network resource in the network resource combination, a search heat level to which the network resources belong;
  • An evaluation module configured to evaluate a combined value of the network resource combination based on a search heat level to which the network resources belong, to obtain an evaluation result
  • the determining module is configured to determine, according to the evaluation result, whether the network resource combination needs to be adjusted.
  • the present invention acquires the search heat level to which each network resource belongs by using the search volume data of each network resource in the network resource combination, and combines the network resource combination based on the search heat level to which each network resource belongs. Based on the evaluation results, it is judged whether it is necessary to adjust the network resource combination, and solves the problem of how to determine whether the network resource combination needs to be adjusted, which is beneficial to timely adjusting the network resource combination to give full play to the advantages of network resources.
  • FIG. 1 is a schematic flowchart diagram of a resource combination processing method according to an embodiment of the present invention
  • FIG. 2 is a schematic structural diagram of a resource combination processing apparatus according to another embodiment of the present invention.
  • FIG. 1 is a schematic flowchart diagram of a resource combination processing method according to an embodiment of the present invention. Such as shown in Figure 1, the method includes:
  • the combined value of the network resource combination is evaluated based on the search heat level to which each network resource belongs, to obtain an evaluation result.
  • the network resource combination in this embodiment may be a combination of various information resources of the user, such as a combination of a user's search behavior resource, a user's location resource, a user's required resource, and a user's preference resource, such a user's personal information resource.
  • the combination can fully display the user's attribute information.
  • the network resource combination of the embodiment may also be a combination of various commodity resources, for example, a combination of a jacket, a hat, a shoe, etc., and the combination of the commodity resources can fully satisfy the user's shopping demand, and at the same time enable the merchant. Maximize the benefits.
  • the network resource combination in this embodiment may also be an investment resource combination in the field of investment and wealth management, for example, a stock resource combination.
  • each network resource in the network resource combination may be a stock resource.
  • the stock resource portfolio can be a combination of stocks such as Yinyi Shares, Xinxing Casting, Beijing Culture, and Yituo Shares.
  • network resource combination can produce more beneficial effects.
  • the beneficial effects of network resource combination may change, and the network resource combination needs to be adjusted in time.
  • the adjustment of the network resource combination mainly refers to a process of replacing, deleting, and increasing network resources in a network resource combination to form a new network resource combination.
  • the first choice is to determine if the network resource combination needs to be adjusted.
  • the resource combination processing method provided by this embodiment is positive This is the solution to the problem, to give information on whether the network resource combination needs to be adjusted.
  • the main principle of the method is: based on the search heat of each network resource in the network resource combination, the combined value of the network resource combination is evaluated in real time, and according to the evaluation result, it is determined whether the resource combination needs to be adjusted. Generally speaking, if the evaluation result indicates that the combined value of the network resource combination is high, the network resource combination does not need to be adjusted. If the evaluation result indicates that the combined value of the network resource combination is low, the network resource combination needs to be adjusted. . Wherein, the combined value of the network resource combination can be compared with a certain evaluation index threshold to determine the combination value of the network resource, but is not limited thereto.
  • the search volume data of the network resource can reflect the search heat of the network resource and the user's emotion to the network resource to a certain extent.
  • the high search volume of network resources means that it is highly concerned; the low search volume of network resources means that it is not concerned. If each network resource in a network resource combination is highly concerned, it means that the network resource combination will be highly concerned, reflecting to some extent that the combined value of the network resource combination is higher, and vice versa, if each network resource combination is Network resources are not concerned, which means that the network resource combination will not be noticed, reflecting to some extent that the combined value of the network resource combination is relatively low. Therefore, for a given network resource combination, the combined value of the network resource combination can be evaluated by the search heat of each network resource (ie, the search amount).
  • the search heat is divided into different search heat levels, and the combined value of the network resource combination is evaluated based on the search heat level to which each network resource belongs in the network resource combination.
  • searching the heat of the search heat division it is beneficial to reduce The amount of data processed is reduced, and the processing flow is simplified, which is advantageous for improving processing efficiency.
  • an implementation manner of dividing a search heat level includes: determining a network resource category involved in a network resource combination, and determining, according to a search heat of all available network resources in the network resource category, at least one heat level threshold; Determining at least one heat level threshold to determine a heat level corresponding to the network resource category.
  • the search heat of all available network resources in the network resource category may be filtered to remove the abnormal value, and then the heat level threshold is determined based on the filtered search heat.
  • the filtered search heat can be divided into several equal parts, and the heat level at the equal point is used as a heat level threshold. Assuming that the filtered search heat is halved, the search heat can be divided into five levels, which are high, high, medium, low, and low search heat levels, or can be called five or four levels. , Level 3, Level 2, and Level 1 search heat ratings.
  • the above available network resources actually refer to effective network resources under the network resource category.
  • "effective” and “invalid” can be defined adaptively. For example, taking commodity resources as an example, items that have been removed or not sold can be considered as invalid network resources.
  • a valid period may be defined. Network resources that appear within the valid period or are searched by the user are regarded as valid network resources, and other network resources are regarded as invalid network resources.
  • the search quantity data of each network resource in the network resource combination may be obtained from the search logs of the various search engines, and then the search heat level to which each network resource belongs is obtained according to the search quantity data of each network resource. And further, based on the search heat level to which each network resource belongs, the combined value of the network resource combination is evaluated to obtain an evaluation result, and according to the evaluation result, it is determined whether the network resource combination needs to be performed. Adjustment.
  • the search heat of each network resource may be determined according to the search quantity data of each network resource, and then the search heat of each network resource is determined according to the search heat of each network resource and a preset heat level threshold. grade.
  • determining the search heat of each network resource according to the search quantity data of each network resource may be, but not limited to, the following:
  • the search volume data of the network resource can be directly used as the search heat of the available network resources.
  • the search quantity data of the network resource is numerically processed, for example, exponential or logarithmic or weighted processing is performed on the search quantity data, and the numerically processed result is used as the search heat of the network resource.
  • one unit time may be taken, for example, one day as one unit time, one hour as one unit time, one month as one unit time, etc.;
  • the search temperature in the current unit time is obtained by using the search amount data of at least one unit time before the current unit time.
  • the search popularity of network resources can be calculated according to the following formula.
  • schpop i T represents the search heat of the i-th network resource in the Tth unit time
  • schvol i T-1 represents the i-th network resource in T-1 unit time
  • Search volume data schvol i, T-2 represents the search volume data of the i-th network resource in T-2 unit time.
  • the foregoing is to evaluate the combined value of the network resource combination based on the search heat level to which each network resource belongs, and the implementation process of obtaining the evaluation result includes:
  • the combined value of the network resource combination is evaluated according to at least one evaluation index value to obtain an evaluation result.
  • the search heat level set involved in the stock resource combination includes a total of five search heat levels, namely: high, high, medium, low, and low search heat levels.
  • the combination of the weight and value of each search popularity level in the network search resource set in the above search heat set is used to reflect the contribution of the search heat level to the combined value of the network resource combination.
  • the foregoing calculating at least one evaluation indicator value according to the weight and value of each search heat level in the search heat level set in the network resource combination including:
  • the weight of the search heat level in the network resource combination is obtained, and according to the network resource belonging to the search heat level The independent value of the value of the search heat rating in the network resource portfolio.
  • the resource proportion of the network resources belonging to the search popularity level may be used to indicate the weight of the search heat level in the network resource combination.
  • the sum of the independent values of the network resources belonging to the search popularity level can be used to represent the value of the search heat level in the network resource combination.
  • the resource proportion of network resources can be expressed by the proportion of positions, and the independent value of network resources can be expressed by the yield of each stock.
  • the higher search popularity of the stock of Yinyi Shares The value of the grade in the stock resource portfolio can be expressed as: the yield of Yinyi shares; the value of the medium search heat level to the stock of the emerging cast pipe in the stock resource portfolio can be expressed as: the yield of the emerging cast pipe; and many more.
  • an evaluation index for evaluating the combined value of the network resource combination is determined in advance.
  • the evaluation indicators will vary depending on the application scenario and the network resource category involved in the network resource combination.
  • at least one evaluation index value may be calculated according to the information, and the combined value of the network combination is evaluated according to the obtained evaluation index value. Thereby obtaining the evaluation result.
  • the evaluation result may be information in a form in which the combined value of the network resource combination is higher or lower, or may be a score of a combined value of the network resource combination or the like.
  • the reference resource combination corresponding to the network resource combination may be set in advance, and the weight and value of each search heat level in the reference resource combination may be set.
  • the reference resource combination may be a combination of representative network resources in the industry, for example, according to the number of network resources in the network resource combination and the popularity search level to which each network resource belongs, from the representative network resources of the industry.
  • a network resource that selects the same number and belongs to the same popularity search level constitutes the reference resource combination.
  • a representative independent value and weight can be given by the official, based on which the weight and value of each search heat level in the heat score set in the benchmark resource combination are searched. It can be obtained based on the official value and official weight of the network resources in the benchmark resource combination.
  • the weight and value of each search heat level in the search heat level set involved in the network resource combination may be related to the network resource combination. Searching for the weight and value of each search heat level in the heat resource level set in the reference resource combination, determining at least one intermediate indicator value; and calculating at least one evaluation index value according to the at least one intermediate indicator value.
  • the search heat level may be calculated according to the weight and value of each search heat level in the search heat level set in the network resource combination and the weight and value of each search heat level in the search heat level set in the reference resource combination. At least one weighted value of each search popularity level in the set, for each weighted value, the weighted values of all search heat levels are accumulated to obtain an intermediate indicator value.
  • the weight of the search heat level in the network resource combination and any weight in the weight of the reference resource combination, and the value of the search heat level in the network resource combination and the value in the reference resource combination Multiplying any of the values, each multiplication result is a weighted value of the search heat rating.
  • At least one intermediate indicator value can be calculated using the following formula (2):
  • n can take b or p, for the same reason, l can take b or p, p represents network resource combination, b represents reference resource combination, Q i represents 4 intermediate indicator values, and i has values of 1, 2, 3 , 4.
  • an evaluation index for evaluating the combined value of the network resource combination may be referred to as a search heat configuration contribution index, and the search heat configuration contribution index R search is calculated by the following formula (7):
  • the search heat allocation contribution index is mainly used to measure the total return of the combined stock resource portfolio under the condition that the user determines the ratio of the search heat level in the stock resource combination.
  • the return value of the total return of the benchmark resource portfolio (referred to as excess return).
  • resource selection contribution indicator another evaluation index for evaluating the combined value of the network resource combination
  • R stock is calculated by the following formula (8):
  • the resource selection contribution indicator may also be referred to as a stock selection contribution indicator, and the stock selection contribution indicator is mainly used to measure the combination of the user's self-selected stock ratio.
  • the total return of the stock resource portfolio exceeds the return value of the total return of the benchmark resource portfolio.
  • an interaction contribution indicator another evaluation index for evaluating the combined value of the network resource combination
  • the interaction contribution indicator Rie is calculated by the following formula (9):
  • the interaction contribution indicator is mainly used to measure the ratio of the search heat level in the user's self-determined stock resource combination and the condition of selecting the stocks independently, and the total of the combined stock resource combinations.
  • the at least one evaluation index value it can be determined whether the network resource combination is reasonable and whether adjustment is needed. For example, the at least one evaluation index value may be compared with a preset evaluation index threshold. If at least one evaluation index value is less than the corresponding evaluation index threshold, the network resource combination is considered to be adjusted. Network resource combinations do not need to be adjusted. This embodiment only cites a relatively simple manner of judgment, and is not limited thereto.
  • the combined value of the network resource combination may be evaluated according to the search heat level to which each network resource belongs in the network resource combination in a single cycle, or may be based on the network resources of the multiple cycles simultaneously.
  • the search heat rating evaluates the combined value of the network resource combination.
  • a multi-cycle for evaluating a network resource combination is referred to as an evaluation period, and the evaluation period includes a plurality of single periods.
  • ⁇ t represents the weight coefficient in the t-th cycle
  • N represents the number of cycles included in the evaluation period
  • R p,t represents the yield of the network resource combination in the t-th cycle
  • R b,t represents the yield of the benchmark resource combination in the t-th cycle
  • R p represents the rate of return of the network resource combination during the evaluation period
  • R b represents the rate of return of the benchmark resource combination during the evaluation period
  • the implementation method of evaluating the combined value of the network resource combination by the evaluation index value in a single cycle is applicable to the buy-holding stock resource combination with a lower frequency of the adjustment.
  • the implementation method of evaluating the combined value of the network resource combination by the evaluation index value in a plurality of cycles is applicable to the transaction type stock resource combination with a higher frequency of the adjustment.
  • the method provided by the embodiment is applied to the field of investment and wealth management, and can not only determine whether it is necessary to adjust the wealth management investment portfolio, promote the optimization of the wealth management investment portfolio, but also facilitate the judgment of the ability of the financial management specialist who provides the financial investment portfolio, such as individual stocks.
  • the ability to select, the search heat rating ratio, and the comprehensive ability will help to provide reference advice for ordinary investors, so that ordinary investors can choose a wealth management commissioner and a wealth management portfolio.
  • FIG. 2 is a schematic structural diagram of a resource combination processing apparatus according to an embodiment of the present invention. As shown in FIG. 2, the device includes an acquisition module 21, an evaluation module 22, and a determination module 23.
  • the obtaining module 21 is configured to use, according to search volume data of each network resource in the network resource combination, Obtain the search heat level to which each network resource belongs.
  • the evaluation module 22 is configured to evaluate the combined value of the network resource combination based on the search heat level to which each network resource acquired by the obtaining module 21 belongs to obtain an evaluation result.
  • the determining module 23 is configured to determine, according to the evaluation result obtained by the evaluation module 22, whether the network resource combination needs to be adjusted.
  • the obtaining module 21 is specifically configured to:
  • the search heat level to which each network resource belongs is determined according to the search heat of each network resource and the preset heat level threshold.
  • the obtaining module 21 determines, when determining the search heat of each network resource according to the search quantity data of each network resource, specifically, determining, according to formula (1), the search heat of each network resource.
  • the formula (1) reference can be made to the aforementioned method embodiments.
  • the obtaining module 21 is further configured to: before determining the search heat level to which each network resource belongs according to the search heat of each network resource and the preset heat level threshold;
  • At least one heat level threshold is determined according to the search heat of all available network resources under the network resource category.
  • the evaluation module 22 is specifically operable to:
  • the combined value of the network resource combination is evaluated according to at least one evaluation index value to obtain an evaluation result.
  • the evaluation module 22 obtains the weight and value of each search heat level in the network resource combination in the search heat level set, the evaluation module 22 is specifically used to:
  • the weight of the search heat level in the network resource combination is obtained, and according to the independent value of the network resources belonging to the search heat level , to obtain the value of the search heat level in the network resource combination.
  • the evaluation module 22 may use the resource proportion of the network resources belonging to the search popularity level to indicate the weight of the search heat level in the network resource combination. Similarly, the evaluation module 22 can use the sum of the independent values of the network resources belonging to the search popularity level to indicate the value of the search heat level in the network resource combination.
  • the evaluation module 22 calculates at least one evaluation index value according to the weight and value of each search heat level in the network heat resource level in the search heat level set
  • the evaluation module 22 is specifically configured to:
  • the foregoing reference resource combination may be a combination of representative network resources of the industry, for example, according to the number of network resources in the network resource combination and the heat to which each network resource belongs.
  • the search level which selects the same number of network resources from the industry and belongs to the same heat search level to form the reference resource combination.
  • a representative independent value and weight can be given by the official, based on which the weight and value of each search heat level in the heat score set in the benchmark resource combination are searched. It can be obtained based on the official value and official weight of the network resources in the benchmark resource combination.
  • the evaluation module 22 may calculate the weight and value of each search heat level in the network resource combination according to the weight and value of each search heat level in the search heat level set according to each search heat level in the search heat level set. Searching at least one weighted value of each search popularity level in the heat level set, for each weighted value, summing the weighted values of all search heat levels to obtain an intermediate indicator value.
  • the weight of the search heat level in the network resource combination and any weight in the weight of the reference resource combination, and the value of the search heat level in the network resource combination and the value in the reference resource combination Multiplying any of the values, each multiplication result is a weighted value of the search heat rating.
  • the evaluation module 22 can calculate the intermediate indicator value according to the above formulas (2)-(6).
  • the evaluation module 22 may calculate at least one evaluation index value according to the above formulas (7)-(10).
  • the evaluation module 22 calculates at least one evaluation index value according to the weight and value of each search heat level in the network heat resource level in the search heat level set
  • the evaluation module 22 is specifically configured to:
  • the weight of each search popularity level in the network resource combination based on the search heat level set Reconfirming the weight and value of each search popularity level in the search heat level set in the benchmark resource combination, and determining at least one intermediate indicator value;
  • each evaluation index value in each period is separately weighted and summed to obtain at least one evaluation index value in the evaluation period.
  • the evaluation module 22 may calculate a total excess return indicator, a search heat allocation contribution indicator, and a resource selection contribution indicator in the evaluation period according to the formulas (11)-(13), respectively.
  • the network resource combination in this embodiment may be an investment resource combination in the field of investment and wealth management, for example, a stock resource combination.
  • each network resource in the network resource combination may be a stock resource.
  • the stock resource portfolio can be a combination of stocks such as Yinyi Shares, Xinxing Casting, Beijing Culture, and Yituo Shares.
  • the resource combination processing device obtains the search heat level to which each network resource belongs by using the search quantity data of each network resource in the network resource combination, and based on the search heat level to which each network resource belongs, the network resource combination is The combined value is evaluated. According to the evaluation result, it is judged whether the network resource combination needs to be adjusted, and how to determine whether the network resource combination needs to be adjusted is solved, which is beneficial to timely adjusting the network resource combination to give full play to the advantages of the network resource.
  • the disclosed system, apparatus, and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of hardware plus software functional units.
  • the above-described integrated unit implemented in the form of a software functional unit can be stored in a computer readable storage medium.
  • the above software functional unit is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to perform the methods of the various embodiments of the present invention. Part of the steps.
  • the foregoing storage medium includes: a USB flash drive, a mobile hard disk, a read-only memory (ROM), and a random access memory (Random Access Memory, A variety of media that can store program code, such as RAM, disk, or optical disk.

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Abstract

一种资源组合处理方法、装置、设备和计算机存储介质，所述方法包括：根据网络资源组合中各网络资源的搜索量数据，获取各网络资源所属的搜索热度等级（101）；以各网络资源所属的搜索热度等级为依据，对网络资源组合的组合价值进行评价，以获得评价结果（102）；根据评价结果，判断是否需要对网络资源组合进行调整（103）。采用上述技术方案，可以解决如何确定是否需要对网络资源组合进行调整的问题，有利于对网络资源组合进行及时调整。

Description

资源组合处理方法、装置、设备及计算机存储介质
本申请要求了申请日为2015年09月29日，申请号为201510633816.2发明名称为“资源组合处理方法及装置”的中国专利申请的优先权。
技术领域
本发明涉及互联网技术领域，尤其涉及一种资源组合处理方法、装置、设备及计算机存储介质。
背景技术
随着信息科技突飞猛进，网络资源呈现爆炸性增长。网络资源的组合可能会产生更多有益效果。例如，在信息推送领域，组合使用用户的位置资源和需求资源，可以向用户推送更加符合用户需求的信息，有利于提高信息推送的准确性。又例如，在投资理财领域，组合购买多种理财产品，可以降低投资风险，有利于提高投资收益。
在不同时期或不同场景，网络资源组合所能带来的有益效果可能不同，这意味着网络资源的组合不是一成不变的，需要不断调整网络资源组合。但是，如何确定是否需要对网络资源组合进行调整是首要解决的问题。
发明内容
本发明的多个方面提供一种资源组合处理方法及装置，用以判断是否需要对网络资源组合进行调整，便于对网络资源组合进行及时调整。
本发明的一方面，提供一种资源组合处理方法，包括：
根据网络资源组合中各网络资源的搜索量数据，获取所述各网络资源所属的搜索热度等级；
以所述各网络资源所属的搜索热度等级为依据，对所述网络资源组合的组合价值进行评价，以获得评价结果；
根据所述评价结果，判断是否需要对所述网络资源组合进行调整。
本发明的另一方面，提供一种资源组合处理装置，包括：
获取模块，用于根据网络资源组合中各网络资源的搜索量数据，获取所述各网络资源所属的搜索热度等级；
评价模块，用于以所述各网络资源所属的搜索热度等级为依据，对所述网络资源组合的组合价值进行评价，以获得评价结果；
判断模块，用于根据所述评价结果，判断是否需要对所述网络资源组合进行调整。
由上述技术方案可知，本发明通过网络资源组合中各网络资源的搜索量数据，获取各网络资源所属的搜索热度等级，以各网络资源所属的搜索热度等级为依据，对网络资源组合的组合价值进行评价，根据评价结果，判断是否需要对网络资源组合进行调整，解决了如何确定是否需要对网络资源组合进行调整的问题，有利于及时调整网络资源组合，以充分发挥网络资源的优势。
附图说明
图1为本发明一实施例提供的资源组合处理方法的流程示意图；
图2为本发明另一实施例提供的资源组合处理装置的结构示意图。
具体实施方式
为了使本发明的目的、技术方案和优点更加清楚，下面结合附图和具体实施例对本发明进行详细描述。
图1为本发明一实施例提供的资源组合处理方法的流程示意图。如 图1所示，该方法包括：
101、根据网络资源组合中各网络资源的搜索量数据，获取各网络资源所属的搜索热度等级。
102、以各网络资源所属的搜索热度等级为依据，对网络资源组合的组合价值进行评价，以获得评价结果。
103、根据上述评价结果，判断是否需要对网络资源组合进行调整。
本实施例不限定网络资源组合所涉及的网络资源类别，可以是各种类别的网络资源的组合。例如，本实施例的网络资源组合可以是用户各种信息资源的组合，例如用户的搜索行为资源、用户的位置资源、用户的需求资源、用户的偏好资源等组合，这种用户个人信息的资源组合可以充分展示用户的属性信息。又例如，本实施例的网络资源组合还可以是各种商品资源的组合，例如可以是上衣、帽子、鞋子等组合，这种商品资源的组合可以充分满足用户的购物需求，同时也能使商家利益最大化。又例如，本实施例的网络资源组合还可以是投资理财领域中的投资资源组合，例如，股票资源组合，相应的，网络资源组合中的各网络资源可以是股票资源。举例说明，股票资源组合可以是银亿股份、新兴铸管、北京文化、一拖股份等各支股票的组合。
与单个网络资源相比，网络资源组合能够产生更多的有益效果，但是在不同时期或不同场景，网络资源组合所能带来的有益效果可能发生变化，需要及时对网络资源组合进行调整。所述对网络资源组合的调整主要是指替换、删除、增加网络资源组合中的网络资源，以形成新的网络资源组合的过程。在对网络资源组合进行调整之前，首选需要确定是否需要对网络资源组合进行调整。本实施例提供的资源组合处理方法正 是解决该问题的，用以给出是否需要对网络资源组合进行调整的信息。该方法的主要原理是：基于网络资源组合中各网络资源的搜索热度，对网络资源组合的组合价值进行实时评价，根据评价结果，判断是否需要对资源组合进行调整。一般来说，如果评价结果表示该网络资源组合的组合价值很高，则不需要对网络资源组合进行调整，如果评价结果表示该网络资源组合的组合价值很低，则需要对网络资源组合进行调整。其中，可以将网络资源组合的组合价值与一定评价指标阈值进行比较，来判断网络资源的组合价值的高低，但不限于此。
下面对本实施例方法所依据的原理以及流程进行详细说明。
在“互联网+”概念如火如荼的今天，作为互联网的核心数据之一，搜索量数据的价值日益凸显。网络资源的搜索量数据一定程度上可以反映出该网络资源的搜索热度以及用户对该网络资源的情绪。网络资源的搜索量高，代表着其被高度关注；网络资源的搜索量低，代表着其不被关注。如果一个网络资源组合中各网络资源均被高度关注，意味着该网络资源组合会被高度关注，在一定程度上反映出该网络资源组合的组合价值较高，反之，若一个网络资源组合中各网络资源均不被关注，意味着该网络资源组合不会被关注，在一定程度上反映出该网络资源组合的组合价值相对较低。因此，对于一个既定的网络资源组合，可以通过其包含的各网络资源的搜索热度(即搜索量的高低)来评价该网络资源组合的组合价值。
在本实施例中，将搜索热度划分为不同的搜索热度等级，以网络资源组合中各网络资源所属的搜索热度等级为依据，对网络资源组合的组合价值进行评价。其中，通过对搜索热度划分搜索热度等级，有利于减 少所处理的数据量，简化处理流程，有利于提高处理效率。
可选的，一种划分搜索热度等级的实施方式包括：确定网络资源组合涉及的网络资源类别，根据该网络资源类别下所有可用网络资源的搜索热度，确定至少一个热度等级门限；之后，根据所确定出的至少一个热度等级门限，确定该网络资源类别对应的热度等级。
可选的，在确定至少一个热度等级门限之前，可以对上述网络资源类别下所有可用网络资源的搜索热度进行过滤，以去除异常数值，然后基于过滤后的搜索热度确定热度等级门限。例如，可以对过滤后的搜索热度进行若干等分，将等分点处的热度等级作为一个热度等级门限。假设将过滤后的搜索热度进行五等分，则可以将搜索热度划分为五个等级，分别为高、较高、中等、较低和低搜索热度等级，或者也可以称为五级、四级、三级、二级和一级搜索热度等级。
上述可用网络资源实际上是指该网络资源类别下的有效网络资源。根据应用场景的不同，可以适应性的对“有效”和“无效”进行定义。举例说明，以商品资源为例，可以将已经下架或不在销售的商品视为无效网络资源。又例如，可以定义有效期间，在有效期间内出现或者被用户搜索过的网络资源视为有效网络资源，其它网络资源视为无效网络资源。
基于上述划分的搜索热度等级，可以从各种搜索引擎的搜索日志中获取网络资源组合中各网络资源的搜索量数据，然后根据各网络资源的搜索量数据，获取各网络资源所属的搜索热度等级；进而以各网络资源所属的搜索热度等级为依据，对网络资源组合的组合价值进行评价，以获得评价结果，并根据该评价结果，判断是否需要对网络资源组合进行 调整。
在一可选实施方式中，可以根据各网络资源的搜索量数据，确定各网络资源的搜索热度，进而根据各网络资源的搜索热度和预设的热度等级门限，确定各网络资源所属的搜索热度等级。
进一步，上述根据各网络资源的搜索量数据，确定各网络资源的搜索热度可以采用但不限于以下方式：
在一种方式中，可以直接将网络资源的搜索量数据作为可用网络资源的搜索热度。
在另一种方式中，对网络资源的搜索量数据进行数值处理，例如对搜索量数据取指数或对数或加权处理，将数值处理后的结果作为网络资源的搜索热度。
在又一种方式中，考虑到网络资源的搜索量数据是不断变化的，可以取一单位时间，例如一天作为一个单位时间，一小时作为一个单位时间，一个月作为一个单位时间等；然后，利用当前单位时间之前至少一个单位时间内的搜索量数据，获得当前单位时间内的搜索热度。例如，可以根据以下公式，计算网络资源的搜索热度。
schpopi,T＝schvoli,T-1/schvoli,T-2    (1)
在上述公式(1)中，schpopi,T表示第i个网络资源在第T个单位时间内的搜索热度；schvoli,T-1表示第i个网络资源在T-1个单位时间内的搜索量数据；schvoli,T-2表示第i个网络资源在T-2个单位时间内的搜索量数据。
值得说明的是，上述几种方式不仅可用于计算网络资源组合中各网络资源的搜索热度，也可以用于计算网络资源组合涉及的网络资源类别下的可用网络资源的搜索热度。
在一可选实施方式中，上述以各网络资源所属的搜索热度等级为依据，对网络资源组合的组合价值进行评价，以获得评价结果的实施过程包括：
对各网络资源所属的搜索热度等级进行统计，以确定网络资源组合涉及的搜索热度等级集合；
获取搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值；
根据搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值，计算至少一个评价指标值；
根据至少一个评价指标值，对网络资源组合的组合价值进行评价，以获得评价结果。
以网络资源组合为100万的股票资源组合为例，该股票资源组合如表1所示：
表1
Figure PCTCN2015098084-appb-000001
由上述表1可知，该股票资源组合涉及的搜索热度等级集合一共包括五个搜索热度等级，分别是：较高、高、中等、较低和低搜索热度等级。
上述搜索热度集合中每个搜索热度等级在网络资源组合中的权重及价值相结合，用于反应指该搜索热度等级对网络资源组合的组合价值的贡献量。可选的，上述根据搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值，计算至少一个评价指标值，包括：
对于搜索热度等级集合中的每个搜索热度等级，根据属于该搜索热度等级的网络资源的资源占比，获取该搜索热度等级在网络资源组合中的权重，并根据属于该搜索热度等级的网络资源的独立价值，获取搜索热度等级在网络资源组合中的价值。
例如，可以用属于该搜索热度等级的网络资源的资源占比，表示该搜索热度等级在网络资源组合中的权重。同理，可以用属于该搜索热度等级的网络资源的独立价值之和，表示该搜索热度等级在网络资源组合中的价值。
仍以上述股票资源组合为例，网络资源的资源占比可以通过持仓量的占比来表示，网络资源的独立价值可以通过每只股票的收益率表示。基于此，对于银亿股份这只股票所属的较高搜索热度等级在股票资源组合中的权重可表示为：33200/(33200+49800+28500+73200+59100)＝332/2438；对于新兴铸管这只股票所属的中等搜索热度等级在股票资源组合中的权重可表示为：49800/(33200+49800+28500+73200+59100)＝498/2438；等等。基于此，对于银亿股份这只股票所属的较高搜索热度 等级在股票资源组合中的价值可表示为：银亿股份的收益率；对于新兴铸管这只股票所属的中等搜索热度等级在股票资源组合中的价值可表示为：新兴铸管的收益率；等等。
在本实施例中，预先确定用于评价网络资源组合的组合价值的评价指标。根据应用场景以及网络资源组合所涉及网络资源类别的不同，评价指标也会有所不同。在获得搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值之后，可以根据该信息计算至少一个评价指标值，根据获得的评价指标值，对网络组合的组合价值进行评价，从而获得评价结果。所述评价结果可以是该网络资源组合的组合价值较高或较低等形式的信息，或者也可以是该网络资源组合的组合价值的得分等。
进一步，为了便于对网络资源组合的组合价值进行评价，可以预先设定与该网络资源组合对应的基准资源组合，并设定各搜索热度等级在基准资源组合中的权重及价值。所述基准资源组合可以是由业界有代表性的网络资源组合而成，例如可以根据网络资源组合中网络资源的个数以及各网络资源所属的热度搜索等级，从业界具有代表性的网络资源中选择相同个数且属于相同热度搜索等级的网络资源组成该基准资源组合。对于业界具有代表性的每个网络资源，可以由官方给定的一个具有代表性的独立价值和权重，基于此，搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，可以基于基准资源组合中网络资源的官方价值及官方权重来获得。
基于上述，可以根据网络资源组合涉及的搜索热度等级集合中每个搜索热度等级在该网络资源组合中的权重及价值与网络资源组合涉及的 搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，确定至少一个中间指标值；根据至少一个中间指标值，计算至少一个评价指标值。
具体的，可以根据搜索热度等级集合中每个搜索热度等级在该网络资源组合中的权重及价值与搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，计算搜索热度等级集合中的每个搜索热度等级的至少一种加权价值，对每种加权价值，将所有搜索热度等级的该种加权价值进行累加，以获得一个中间指标值。其中，可以将该搜索热度等级在该网络资源组合中的权重和在基准资源组合中权重中的任一权重，与该搜索热度等级在该网络资源组合中的价值和在基准资源组合中的价值中的任一价值相乘，每种相乘结果即为该搜索热度等级的一种加权价值。
例如，可以采用如下公式(2)计算至少一个中间指标值：
Figure PCTCN2015098084-appb-000002
其中，m可以取b或p，同理，l可以取b或p，p表示网络资源组合，b表示基准资源组合，Qi表示4个中间指标值，i的取值为1,2,3,4。
具体的，可以获得以下4个中间指标值：
Figure PCTCN2015098084-appb-000003
Figure PCTCN2015098084-appb-000004
Figure PCTCN2015098084-appb-000005
Figure PCTCN2015098084-appb-000006
在上述公式(3)-(6)中，
Figure PCTCN2015098084-appb-000007
表示搜索热度等级j在网络资源组合中的权重；
Figure PCTCN2015098084-appb-000008
表示搜索热度等级j在基准资源组合中的权重；
Figure PCTCN2015098084-appb-000009
表示搜索热度等级j在网络资源组合中的价值；
Figure PCTCN2015098084-appb-000010
表示搜索热度等级j在基准资源组合中的价值。以表1所示股票资源组合为例，则可以采用上述公式计算出该股票资源组合对应的4个中间指标值。
基于上述4个中间指标值，一个用于评价网络资源组合的组合价值的评价指标可以称为搜索热度配置贡献指标，该搜索热度配置贡献指标Rsearch采用如下公式(7)计算获得：
Figure PCTCN2015098084-appb-000011
以网络资源组合为股票资源组合为例，则搜索热度配置贡献指标主要用于衡量在用户自主决定股票资源组合中搜索热度等级的配比的条件下，所组合出的股票资源组合的总收益超出基准资源组合的总收益的收益值(简称为超额收益)。
基于上述4个中间指标值，另一个用于评价网络资源组合的组合价值的评价指标可以称为资源选择贡献指标，该资源选择贡献指标Rstock采用如下公式(8)计算获得：
Figure PCTCN2015098084-appb-000012
以网络资源组合为股票资源组合为例，则资源选择贡献指标还可称为个股选择贡献指标，该个股选择贡献指标主要用于衡量在用户自主选择个股的配比的条件下，所组合出的股票资源组合的总收益超出基准资源组合的总收益的收益值。
基于上述4个中间指标值，另一个用于评价网络资源组合的组合价 值的评价指标可以称为交互作用贡献指标，该交互作用贡献指标Rie采用如下公式(9)计算获得：
Figure PCTCN2015098084-appb-000013
以网络资源组合为股票资源组合为例，则交互作用贡献指标主要用于衡量在用户自主决定股票资源组合中搜索热度等级的配比并自主选择个股的条件，所组合出的股票资源组合的总收益超出基准资源组合的总收益的收益值。其中，股票资源组合的超额收益一部分来自于搜索热度等级的配比，一部分来自于个股选择。
基于上述4个中间指标值，另一个用于评价网络资源组合的组合价值的评价指标可以称为总超额收益指标，该总超额收益指标Rtoal采用如下公式(10)计算获得：
Figure PCTCN2015098084-appb-000014
通过上述至少一个评价指标值，可以判断网络资源组合是否合理，是否需要调整。例如，可以将上述至少一个评价指标值与预设的评价指标门限值进行比较，若至少一个评价指标值小于相应的评价指标门限值，则认为该网络资源组合需要调整，反之，认为该网络资源组合不需要调整。本实施例只是列举一种较为简单的判断方式，并不限于此。
进一步，考虑到网络资源组合的周期性，可以根据单周期内网络资源组合中各网络资源所属的搜索热度等级对网络资源组合的组合价值进行评价，也可以同时基于多周期内各网络资源所属的搜索热度等级对网络资源组合的组合价值进行评价。为便于描述，将用于评价网络资源组合的多周期称为评价期间，该评价期间包括多个单周期。
具体的，根据搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值与所述搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，确定至少一个中间指标值；根据至少一个中间指标值，计算评价期间包含的每个周期内的至少一个评价指标值；计算每个周期内的至少一个评价指标值中每个评价指标值对应的权重系数；根据每个周期内每个评价指标值对应的权重系数，对每个周期内每个评价指标值分别进行加权求和，以获得评价周期内的至少一个评价指标值，然后基于该评价期间内的至少一个评价指标值，对网络资源组合的组合价值进行评价。
上述根据每个周期内每个评价指标值对应的权重系数，对每个周期内每个评价指标值分别进行加权求和，以获得评价周期内的至少一个评价指标值的过程如下：
分别根据公式(11)-(13)，计算评价期间内的总超额收益指标、搜索热度配置贡献指标和资源选择贡献指标。
Figure PCTCN2015098084-appb-000015
Figure PCTCN2015098084-appb-000016
Figure PCTCN2015098084-appb-000017
在上述公式中，βt表示在第t周期内的权重系数，N表示评价期间包含的周期数，且
Figure PCTCN2015098084-appb-000018
上述公式中，
Figure PCTCN2015098084-appb-000019
Rp,t表示第t周期网络资源组合的收益率，Rb,t表示第t周期基准资源组合的收益率。
上述公式中，
Figure PCTCN2015098084-appb-000020
Rp表示评价期间内网络资源组合的收益率，
Figure PCTCN2015098084-appb-000021
Rb表示评价期间内基准资源组合的收益率，
Figure PCTCN2015098084-appb-000022
其中，以单个周期内的评价指标值，对网络资源组合的组合价值进行评价的实施方式，适用于调仓频率较低的买入持有型股票资源组合。以多个周期内的评价指标值，对网络资源组合的组合价值进行评价的实施方式，适用于调仓频率较高的交易型股票资源组合。
另外，本实施例提供的方法应用于投资理财领域，不仅可以判断出是否需要调整理财投资组合，促进理财投资组合的最优化，而且有利于判断提供该理财投资组合的理财专员的能力，例如个股选择能力、搜索热度等级配比能力以及综合能力等，有利于为普通投资者提供参考建议，以便普通投资者选择理财专员及理财投资组合。
需要说明的是，对于前述的各方法实施例，为了简单描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明并不受所描述的动作顺序的限制，因为依据本发明，某些步骤可以采用其他顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作和模块并不一定是本发明所必须的。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
图2为本发明一实施例提供的资源组合处理装置的结构示意图。如图2所示，该装置包括：获取模块21、评价模块22和判断模块23。
获取模块21，用于根据网络资源组合中各网络资源的搜索量数据， 获取各网络资源所属的搜索热度等级。
评价模块22，用于以获取模块21获取的各网络资源所属的搜索热度等级为依据，对网络资源组合的组合价值进行评价，以获得评价结果。
判断模块23，用于根据评价模块22获得的评价结果，判断是否需要对网络资源组合进行调整。
在一可选实施方式中，获取模块21具体可用于：
根据各网络资源的搜索量数据，确定各网络资源的搜索热度；
根据各网络资源的搜索热度和预设的热度等级门限，确定各网络资源所属的搜索热度等级。
在一可选实施方式中，获取模块21在根据各网络资源的搜索量数据，确定各网络资源的搜索热度时，具体用于：根据公式(1)，确定各网络资源的搜索热度。关于公式(1)的描述，可参见前述方法实施例。
在一可选实施方式中，获取模块21在根据各网络资源的搜索热度和预设的热度等级门限，确定各网络资源所属的搜索热度等级之前，还用于：
确定网络资源组合涉及的网络资源类别；
根据网络资源类别下所有可用网络资源的搜索热度，确定至少一个热度等级门限。
在一可选实施方式中，评价模块22具体可用于：
对各网络资源所属的搜索热度等级进行统计，以确定网络资源组合涉及的搜索热度等级集合；
获取搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值；
根据搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值，计算至少一个评价指标值；
根据至少一个评价指标值，对网络资源组合的组合价值进行评价，以获得评价结果。
进一步，评价模块22在获取搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值时，具体用于：
对于搜索热度等级集合中的每个搜索热度等级，根据属于搜索热度等级的网络资源的资源占比，获取搜索热度等级在网络资源组合中的权重，并根据属于搜索热度等级的网络资源的独立价值，获取搜索热度等级在网络资源组合中的价值。
例如，评价模块22可以用属于该搜索热度等级的网络资源的资源占比，表示该搜索热度等级在网络资源组合中的权重。同理，评价模块22可以用属于该搜索热度等级的网络资源的独立价值之和，表示该搜索热度等级在网络资源组合中的价值。
进一步，评价模块22在根据搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值，计算至少一个评价指标值时，具体用于：
根据搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值与搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，确定至少一个中间指标值；
根据至少一个中间指标值，计算至少一个评价指标值。
上述基准资源组合可以是由业界有代表性的网络资源组合而成，例如可以根据网络资源组合中网络资源的个数以及各网络资源所属的热度 搜索等级，从业界具有代表性的网络资源中选择相同个数且属于相同热度搜索等级的网络资源组成该基准资源组合。对于业界具有代表性的每个网络资源，可以由官方给定的一个具有代表性的独立价值和权重，基于此，搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，可以基于基准资源组合中网络资源的官方价值及官方权重来获得。
具体的，评价模块22可以根据搜索热度等级集合中每个搜索热度等级在该网络资源组合中的权重及价值与搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，计算搜索热度等级集合中的每个搜索热度等级的至少一种加权价值，对每种加权价值，将所有搜索热度等级的该种加权价值进行累加，以获得一个中间指标值。其中，可以将该搜索热度等级在该网络资源组合中的权重和在基准资源组合中权重中的任一权重，与该搜索热度等级在该网络资源组合中的价值和在基准资源组合中的价值中的任一价值相乘，每种相乘结果即为该搜索热度等级的一种加权价值。
例如，评价模块22可以根据上述公式(2)-(6)来计算中间指标值。
进一步，评价模块22可以根据上述公式(7)-(10)来计算至少一个评价指标值。
进一步，评价模块22在根据搜索热度等级集合中每个搜索热度等级在网络资源组合中的权重及价值，计算至少一个评价指标值时，具体用于：
根据搜索热度等级集合中每个搜索热度等级在网络资源组合中的权 重及价值与搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，确定至少一个中间指标值；
根据至少一个中间指标值，计算评价期间包含的每个周期内的至少一个评价指标值；
计算每个周期内的至少一个评价指标值中每个评价指标值对应的权重系数；
根据每个周期内每个评价指标值对应的权重系数，对每个周期内每个评价指标值分别进行加权求和，以获得评价周期内的至少一个评价指标值。
可选的，评价模块22可以分别根据公式(11)-(13)，计算评价期间内的总超额收益指标、搜索热度配置贡献指标和资源选择贡献指标。
可选的，本实施例的网络资源组合可以是投资理财领域中的投资资源组合，例如，股票资源组合，相应的，网络资源组合中的各网络资源可以是股票资源。举例说明，股票资源组合可以是银亿股份、新兴铸管、北京文化、一拖股份等各支股票的组合。
本实施例提供的资源组合处理装置，通过网络资源组合中各网络资源的搜索量数据，获取各网络资源所属的搜索热度等级，以各网络资源所属的搜索热度等级为依据，对网络资源组合的组合价值进行评价，根据评价结果，判断是否需要对网络资源组合进行调整，解决了如何确定是否需要对网络资源组合进行调整的问题，有利于及时调整网络资源组合，以充分发挥网络资源的优势。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例 中的对应过程，在此不再赘述。
在本发明所提供的几个实施例中，应该理解到，所揭露的系统，装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
上述以软件功能单元的形式实现的集成的单元，可以存储在一个计算机可读取存储介质中。上述软件功能单元存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本发明各个实施例所述方法的部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory， RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内，所做的任何修改、等同替换、改进等，均应包含在本发明保护的范围之内。

Claims (20)

  1. 一种资源组合处理方法，其特征在于，包括：
    根据网络资源组合中各网络资源的搜索量数据，获取所述各网络资源所属的搜索热度等级；
    以所述各网络资源所属的搜索热度等级为依据，对所述网络资源组合的组合价值进行评价，以获得评价结果；
    根据所述评价结果，判断是否需要对所述网络资源组合进行调整。
  2. 根据权利要求1所述的方法，其特征在于，所述根据网络资源组合中各网络资源的搜索量数据，获取所述各网络资源所属的搜索热度等级，包括：
    根据所述各网络资源的搜索量数据，确定所述各网络资源的搜索热度；
    根据所述各网络资源的搜索热度和预设的热度等级门限，确定所述各网络资源所属的搜索热度等级。
  3. 根据权利要求2所述的方法，其特征在于，所述根据所述各网络资源的搜索量数据，确定所述各网络资源的搜索热度，包括：
    根据公式schpopi,T＝schvoli,T-1/schvoli,T-2，确定所述各网络资源的搜索热度；
    schpopi,T表示第i个网络资源在第T个单位时间内的搜索热度；
    schvoli,T-1表示第i个网络资源在T-1个单位时间内的搜索量数据；
    schvoli,T-2表示第i个网络资源在T-2个单位时间内的搜索量数据。
  4. 根据权利要求2所述的方法，其特征在于，所述根据所述各网络资源的搜索热度和预设的至少一个热度等级门限，确定所述各网络资源 所属的搜索热度等级之前，包括：
    确定所述网络资源组合涉及的网络资源类别；
    根据所述网络资源类别下所有可用网络资源的搜索热度，确定所述至少一个热度等级门限。
  5. 根据权利要求1-4任一项所述的方法，其特征在于，所述以所述各网络资源所属的搜索热度等级为依据，对所述网络资源组合的组合价值进行评价，以获得评价结果，包括：
    对所述各网络资源所属的搜索热度等级进行统计，以确定所述网络资源组合涉及的搜索热度等级集合；
    获取所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值；
    根据所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值，计算至少一个评价指标值；
    根据所述至少一个评价指标值，对所述网络资源组合的组合价值进行评价，以获得所述评价结果。
  6. 根据权利要求5所述的方法，其特征在于，所述获取所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值，包括：
    对于所述搜索热度等级集合中的每个搜索热度等级，根据属于所述搜索热度等级的网络资源的资源占比，获取所述搜索热度等级在所述网络资源组合中的权重，并根据属于所述搜索热度等级的网络资源的独立价值，获取所述搜索热度等级在所述网络资源组合中的价值。
  7. 根据权利要求5所述的方法，其特征在于，所述根据所述搜索热 度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值，计算至少一个评价指标值，包括：
    根据所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值与所述搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，确定至少一个中间指标值；
    根据所述至少一个中间指标值，计算所述至少一个评价指标值。
  8. 根据权利要求5所述的方法，其特征在于，所述根据所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值，计算至少一个评价指标值，包括：
    根据所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值与所述搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，确定至少一个中间指标值；
    根据所述至少一个中间指标值，计算评价期间包含的每个周期内的至少一个评价指标值；
    计算所述每个周期内的至少一个评价指标值中每个评价指标值对应的权重系数；
    根据所述每个周期内每个评价指标值对应的权重系数，对所述每个周期内每个评价指标值分别进行加权求和，以获得所述评价周期内的至少一个评价指标值。
  9. 根据权利要求1-4任一项所述的方法，其特征在于，所述网络资源组合为股票资源组合，所述网络资源为股票资源。
  10. 一种资源组合处理装置，其特征在于，包括：
    获取模块，用于根据网络资源组合中各网络资源的搜索量数据，获 取所述各网络资源所属的搜索热度等级；
    评价模块，用于以所述各网络资源所属的搜索热度等级为依据，对所述网络资源组合的组合价值进行评价，以获得评价结果；
    判断模块，用于根据所述评价结果，判断是否需要对所述网络资源组合进行调整。
  11. 根据权利要求10所述的装置，其特征在于，所述获取模块具体用于：
    根据所述各网络资源的搜索量数据，确定所述各网络资源的搜索热度；
    根据所述各网络资源的搜索热度和预设的热度等级门限，确定所述各网络资源所属的搜索热度等级。
  12. 根据权利要求11所述的装置，其特征在于，所述获取模块具体用于：
    根据公式schpopi,T＝schvoli,T-1/schvoli,T-2，确定所述各网络资源的搜索热度；
    schpopi,T表示第i个网络资源在第T个单位时间内的搜索热度；
    schvoli,T-1表示第i个网络资源在T-1个单位时间内的搜索量数据；
    schvoli,T-2表示第i个网络资源在T-2个单位时间内的搜索量数据。
  13. 根据权利要求11所述的装置，其特征在于，所述获取模块还用于：
    确定所述网络资源组合涉及的网络资源类别；
    根据所述网络资源类别下所有可用网络资源的搜索热度，确定所述至少一个热度等级门限。
  14. 根据权利要求10-13任一项所述的装置，其特征在于，所述评价模块具体用于：
    对所述各网络资源所属的搜索热度等级进行统计，以确定所述网络资源组合涉及的搜索热度等级集合；
    获取所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值；
    根据所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值，计算至少一个评价指标值；
    根据所述至少一个评价指标值，对所述网络资源组合的组合价值进行评价，以获得所述评价结果。
  15. 根据权利要求14所述的装置，其特征在于，所述评价模块具体用于：
    对于所述搜索热度等级集合中的每个搜索热度等级，根据属于所述搜索热度等级的网络资源的资源占比，获取所述搜索热度等级在所述网络资源组合中的权重，并根据属于所述搜索热度等级的网络资源的独立价值，获取所述搜索热度等级在所述网络资源组合中的价值。
  16. 根据权利要求15所述的装置，其特征在于，所述评价模块具体用于：
    根据所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值与所述搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，确定至少一个中间指标值；
    根据所述至少一个中间指标值，计算所述至少一个评价指标值。
  17. 根据权利要求14所述的装置，其特征在于，所述评价模块具体 用于：
    根据所述搜索热度等级集合中每个搜索热度等级在所述网络资源组合中的权重及价值与所述搜索热度等级集合中每个搜索热度等级在基准资源组合中的权重及价值，确定至少一个中间指标值；
    根据所述至少一个中间指标值，计算评价期间包含的每个周期内的至少一个评价指标值；
    计算所述每个周期内的至少一个评价指标值中每个评价指标值对应的权重系数；
    根据所述每个周期内每个评价指标值对应的权重系数，对所述每个周期内每个评价指标值分别进行加权求和，以获得所述评价周期内的至少一个评价指标值。
  18. 根据权利要求10-13任一项所述的装置，其特征在于，所述网络资源组合为股票资源组合，所述网络资源为股票资源。
  19. 一种设备，包括：
    一个或多个处理器；
    存储器；
    一个或多个程序，所述一个或多个程序存储在所述存储器中，当被所述一个或多个处理器执行时，执行以下操作：
    根据网络资源组合中各网络资源的搜索量数据，获取所述各网络资源所属的搜索热度等级；
    以所述各网络资源所属的搜索热度等级为依据，对所述网络资源组合的组合价值进行评价，以获得评价结果；
    根据所述评价结果，判断是否需要对所述网络资源组合进行调整。
  20. 一种非易失性计算机存储介质，所述计算机存储介质存储有一个或多个程序，当所述一个或多个程序被一个设备执行时，使得所述设备执行以下操作：
    根据网络资源组合中各网络资源的搜索量数据，获取所述各网络资源所属的搜索热度等级；
    以所述各网络资源所属的搜索热度等级为依据，对所述网络资源组合的组合价值进行评价，以获得评价结果；
    根据所述评价结果，判断是否需要对所述网络资源组合进行调整。
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EP3358473A1 (en) 2018-08-08
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CN105243124A (zh) 2016-01-13
US20170286428A1 (en) 2017-10-05
JP6303231B2 (ja) 2018-04-04
EP3358473A4 (en) 2019-04-24
CN105243124B (zh) 2018-11-09
US10521437B2 (en) 2019-12-31

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