WO2018188545A1 - 保险事故理赔处理方法、装置和理赔服务器 - Google Patents

保险事故理赔处理方法、装置和理赔服务器 Download PDF

Info

Publication number
WO2018188545A1
WO2018188545A1 PCT/CN2018/082286 CN2018082286W WO2018188545A1 WO 2018188545 A1 WO2018188545 A1 WO 2018188545A1 CN 2018082286 W CN2018082286 W CN 2018082286W WO 2018188545 A1 WO2018188545 A1 WO 2018188545A1
Authority
WO
WIPO (PCT)
Prior art keywords
accident
page
content
news link
insurance
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2018/082286
Other languages
English (en)
French (fr)
Inventor
周钦雄
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Ping An Technology Shenzhen Co Ltd
Original Assignee
Ping An Technology Shenzhen Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ping An Technology Shenzhen Co Ltd filed Critical Ping An Technology Shenzhen Co Ltd
Publication of WO2018188545A1 publication Critical patent/WO2018188545A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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
    • G06Q40/08—Insurance

Definitions

  • the present application relates to the field of computer technology, and in particular, to an insurance accident claim processing method, apparatus, and claims server.
  • an insurance accident claim processing method, apparatus, and claims server are provided.
  • An insurance accident claim processing method includes:
  • the claim task is generated according to the to-be-resolved accident, and the claim task is sent to the claim terminal.
  • An insurance accident claim processing device includes:
  • a content collection module configured to acquire a data table, where the data table includes a news link of a plurality of websites; use the news link to access a page of the plurality of websites, and crawl the page content in the plurality of pages;
  • a big data analysis module for performing big data analysis on various page contents to obtain content related to insurance accidents
  • the claim module is configured to: if the claim-to-claim event is identified according to the content related to the insurance accident, generate a claim task according to the to-be-resolved accident, and send the claim task to the claim terminal.
  • a claim server comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor, causing the one or more processors to execute The following steps:
  • the claim task is generated according to the to-be-resolved accident, and the claim task is sent to the claim terminal.
  • One or more non-transitory computer readable storage mediums storing computer readable instructions, when executed by one or more processors, cause one or more processors to perform the steps of:
  • the claim task is generated according to the to-be-resolved accident, and the claim task is sent to the claim terminal.
  • FIG. 1 is an application environment diagram of an insurance accident claim processing method according to one or more embodiments
  • FIG. 2 is a flow chart of an insurance accident claim processing method in accordance with one or more embodiments
  • FIG. 3 is a block diagram of an insurance accident claim processing apparatus in accordance with one or more embodiments
  • FIG. 4 is a block diagram of a claims server in accordance with one or more embodiments.
  • the insurance accident claim processing method provided in the embodiment of the present application can be applied to the application environment as shown in FIG. 1 .
  • the claims server 102 establishes a connection with a plurality of web servers 104 over a network.
  • the claims server 102 establishes a connection with the survey terminal 106 over the network.
  • the claims server 102 and the claims terminal 108 establish a connection over the network.
  • the claims server 102 acquires the portal links of the plurality of website servers 104 using the crawler technology, and obtains the URL list based on the portal links.
  • the claims server 102 filters the list of URLs, obtains a plurality of news links, and records the news links in a data table.
  • the claim server 102 can read the news link in the data table according to the set frequency, access the page provided by the plurality of website servers by using the news link, and crawl the page content in the plurality of pages.
  • the claims server 102 performs big data analysis on the page content captured from the pages of the plurality of website servers 104 to obtain content related to the insurance accident.
  • the claim server 102 acquires the basic information of the accident in the content related to the insurance accident, generates an accident investigation task according to the basic information of the accident, and sends the inspection task to the inspection terminal 106 corresponding to the surveying personnel. If there is a customer who needs a claim, the survey terminal 106 returns the claim customer information to the claims server 102.
  • the claim server 102 records the claims to be settled corresponding to the contents related to the insured event based on the claims customer information.
  • the claim server 102 generates a claim task according to the claim compensation event, and sends the claim task to the claim terminal 108.
  • the claimant provides the client with an active claim service based on the claims task received by the claim terminal. Therefore, the customer can enjoy the claim service in time in the event of an insurance accident.
  • an insurance accident claim processing method is provided.
  • the method is applied to the claim server in FIG. 1 as an example, and specifically includes the following steps:
  • Step 202 Acquire a data table, where the data table includes news links of multiple websites.
  • Step 204 Access a page of multiple websites by using a news link, and crawl the page content in multiple pages.
  • the claims server uses the crawler technology to obtain the portal links of multiple websites, and obtains a list of URLs according to the portal links.
  • the claims server filters the list of URLs to get multiple news links.
  • the claims server can filter the list of URLs using regular expressions.
  • the regular expression adopts a preset format.
  • the preset format is a URL ending with a preset character or a string, such as a URL ending in news, blog, or the like.
  • the claims server logs multiple news links into the data table and stores the data tables in the database.
  • the claims server can read the data table from the database at the set frequency.
  • the claims server scans the data table for news links that have not been crawled.
  • the claims server uses a news link that has not crawled content to access pages of multiple websites, and crawls the page content in multiple pages. Since the claim server uses the news link to capture the content of the page, the content of the page collected by the claim server has a certain timeliness.
  • Step 206 Perform big data analysis on the news content to obtain content related to the insurance accident.
  • the claims server performs big data analysis on the content of pages collected from multiple websites.
  • the claims server can obtain insurance-related keywords, such as car accidents, plane crashes, earthquakes, and explosions.
  • the claim server uses these keywords to perform cluster analysis on the collected page content to obtain content related to the insurance accident.
  • the cluster analysis can adopt the K-means algorithm, and the above keywords are sequentially used as data objects to be iteratively calculated by the K-means algorithm, and the insurance-related content corresponding to each keyword is obtained.
  • Insurance-related content often reflects one or more insured events.
  • the claims server performs big data analysis on the collected page content, which can be regarded as the primary screening of the page content.
  • the claims server needs to further process the content obtained by the screening, that is, the insurance-related content, to identify whether the insurance-related content involves an insurance accident to be settled.
  • the manner of identifying whether there is an insured event to be settled may include a plurality of types.
  • the claim server may acquire the basic information of the accident in the content related to the insurance accident, generate an accident investigation task according to the basic information of the accident, and send the inspection task to the inspection terminal corresponding to the surveying personnel.
  • the surveying personnel go to the scene of the accident to conduct a survey. If there is a customer who needs to make a claim, the survey terminal returns the information to be claimed to the claim server.
  • the claim server receives the to-be-claimed customer information returned by the inspection terminal, and records the to-be-resolved accident corresponding to the content related to the insurance accident according to the customer information to be claimed.
  • the claims server may obtain a picture of the content related to the insured event, identify whether there is a face in the picture, and if so, further identify whether the face is an insured customer image. If so, the claim server records the claims to be settled corresponding to the contents related to the insurance accident according to the customer image.
  • the claims server may also identify the corresponding license plate number in the picture of the vehicle accident. If the identified license plate number is the license plate number of the insured vehicle, the claim server records the to-be-resolved accident corresponding to the content related to the insurance accident according to the license plate number.
  • Step 208 If the claim-resolving accident is identified according to the content related to the insurance accident, the claim task is generated according to the to-be-resolved accident, and the claim task is sent to the claim terminal.
  • the claim server may obtain the corresponding customer information according to the to-be-resolved accident, and extract the corresponding policy information in the database according to the customer information.
  • the claim server generates a claim task based on the policy information and the claim-resolving accident, and sends the claim task to the claim terminal.
  • the claimant provides the client with an active claim service based on the claims task received by the claim terminal. Therefore, the customer can enjoy the claim service in time in the event of an insurance accident.
  • the page content is captured in pages of a plurality of websites by using news links of a plurality of websites. Big data analysis of multiple page content can get content related to insurance accidents. This enables timely access to current insurance-related content. If the claim to be settled is identified according to the content related to the insurance, the claim task may be generated according to the claim for compensation, and the claim task is sent to the claim terminal. The claimant provides the client with an active claim service based on the claims task received by the claim terminal. Therefore, the customer can enjoy the claim service in time in the event of an insurance accident.
  • steps in the flowchart of FIG. 2 are sequentially displayed as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Except as explicitly stated herein, the execution of these steps is not strictly limited, and the steps may be performed in other orders. Moreover, at least some of the steps in FIG. 2 may include a plurality of sub-steps or stages, which are not necessarily performed at the same time, but may be executed at different times, the execution of these sub-steps or stages The order is also not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of the other steps.
  • the step of capturing the page content in the plurality of pages further comprises: calculating an activity weight corresponding to the news link; and the page according to the active weight corresponding to the news link. Scan, if there is a change in the content of the page, update the content of the page that has been crawled.
  • the page content may change over time. The faster the page content changes, the more active the corresponding news link. Take the content of the page as a post in the forum. If the content of the page reflects a hot event, the corresponding news link will be more active. There will usually be more replies on the day after the post is posted and in the next few days. In order to be able to collect more rich page content, the claims server not only needs to crawl the content of the post, but also needs to crawl the content of the reply.
  • the activity of the news link can be reflected by the active weight.
  • the claim server crawls the page content from multiple websites by using multiple news links, it also calculates the active weight corresponding to each news link.
  • the activity of the same news link can be different at different times, and the activity of different news links can be different at different times.
  • the server can calculate the active weight of the news link using the initial weight and time factor corresponding to the news link.
  • the initial weight of each news link in the data table can be the same or different.
  • the time factor can be the same or different.
  • the step of calculating the active weight corresponding to the news link includes: obtaining an initial weight and a time factor corresponding to the news link; scanning the page corresponding to the news link according to the preset frequency, and checking whether the page content is the same; if yes, The initial weight of the news link is added to the time factor to obtain the active weight corresponding to the news link; otherwise, the initial weight of the news link is subtracted from the time factor, and the active weight corresponding to the news link is obtained.
  • the claims server can configure a corresponding initial weight and time factor for each news link in the data table.
  • the claim server can scan the page corresponding to each news link according to the set frequency to check whether the page content is the same. If they are the same, it means that the content of the page has not changed, and the claim server can reduce the frequency of access to the news link.
  • the claim server adds the time weight to the initial weight of the news link, thereby calculating the active weight corresponding to the news link. If the claim server scans the page corresponding to the news link and finds that the content of the page is different from the content that was last crawled, it indicates that the content of the page has changed.
  • the claims server can increase the frequency of access to the news link.
  • the claim server subtracts the time factor from the initial weight of the news link to obtain the active weight corresponding to the news link.
  • Active weights can reflect the activity of news links. Among them, the lower the active weight, the higher the activity of the news link, and the higher the active weight, the lower the activity of the news link.
  • the claims server has an initial weight of 1 for the news link configuration and a time factor of 0.4.
  • the claim server scans the page according to the active weight corresponding to the news link. If the page content still does not change after the scan, the claim server adds the time factor to its current active weight, and calculates the next visit to the corresponding page of the news link. Active weight. By analogy, when the calculated active weight is greater than or equal to the first budget value, it indicates that the page corresponding to the news link is no longer active, and the content of the page may not need to be scanned again. The claims server no longer continues to calculate the active weights corresponding to the news link.
  • the claim server subtracts the time factor from its current active weight, and calculates the active weight of the next visit to the corresponding page of the news link.
  • the calculated active weight is less than or equal to the second preset value, it indicates that the page corresponding to the news link is active.
  • the claim server can no longer continue to calculate the next visit to the news. Linking the active weight of the corresponding page, the second preset value may be directly used as the active weight corresponding to the news link.
  • the claim server may add the time factor to the second preset value according to the method provided above. Calculate the active weight of the next visit to the news link corresponding page until its active weight is greater than or equal to the first preset value.
  • the claim server scans the page according to the active weight corresponding to the news link. If the content of the page is found to be changed, the content of the page is crawled, or only the content that changes on the page is captured, and the captured content has been captured.
  • the content of the page is updated. For example, the updated content may be a comment or a post reply. If the updated content includes content related to the person or address in the accident, it may help to quickly identify an insured event. By updating the content of the crawled page, you can provide assistance for big data analysis and insurance related content.
  • the method further includes: acquiring a picture in the content related to the insurance accident, and identifying the picture; If the face is recognized, it is further recognized whether the face is an insured customer image; if so, the to-be-resolved accident corresponding to the content related to the insurance accident is recorded.
  • the claim server can obtain the basic information of the accident in the content related to the insurance accident according to the result of the big data analysis.
  • Basic information about the accident includes the time of the accident, the location of the accident, and the type of accident.
  • the claim server can generate an accident investigation task based on the basic information of the accident, and send the survey task to the survey terminal corresponding to the survey personnel.
  • the claim server may obtain the survey personnel identification in the corresponding area according to the accident location, and query the survey personnel identification that is familiar with the type of the accident according to the survey personnel identification and the type of the accident.
  • the claim server sends the survey task to the survey terminal corresponding to the survey person identification.
  • the survey personnel familiar with the type of the accident can make a timely investigation to identify whether there is a customer who needs to claim in the accident. If there is a customer who needs to make a claim, the surveying personnel input the information to be claimed by the surveying terminal, and the surveying terminal uploads the customer information to be claimed to the claim server. After receiving the claim customer information, the claim server obtains the corresponding policy information according to the claim customer information. The policy information includes the policy status and the corresponding claims terms. If the policy status is valid and the insured event complies with the terms of the claim, the claim server records the claims to be settled corresponding to the content related to the insured event. This makes it possible to accurately identify the claims to be settled. Since an insurance accident may involve one or more customers to be settled, the survey personnel can be identified by means of assigning survey tasks, and each customer who needs to claim can be accurately identified. This ensures that every customer experiencing an insured event is provided with timely and effective claims services.
  • the method further includes: acquiring a picture in the content related to the insurance accident, and identifying the picture; if in the picture When the face is recognized, it is further recognized whether the face is an insured customer image; if so, the customer information is obtained according to the customer image, and the to-be-resolved accident corresponding to the content related to the insurance accident is recorded.
  • the content related to the insurance accident may include a picture.
  • the claim server extracts the picture of the insurance accident and identifies the picture. If a face is recognized in the picture, it is further determined whether the face is an insured customer image. A large number of insured customer images are stored in the database of the claims server. The image of the insured customer can correspond to one or more policies.
  • the claim server can match the recognized face image with the client image stored in the database, and if the matching value with a certain client image in the database exceeds the threshold, the face image identified from the image is recorded as insured. Customer image.
  • the claim server After the claim server identifies the insured customer image, it obtains the customer information and the corresponding policy information based on the customer image.
  • the policy information includes the policy status and the corresponding claims terms. If the policy status is valid and the insurance accident meets the requirements of the claims clause, the claim server records the claims to be settled corresponding to the contents related to the insurance accident according to the customer information. This makes it possible to accurately identify the claims to be settled. Identifying the claims to be compensated by means of face recognition matching can effectively save the work of the survey personnel and effectively improve the recognition efficiency of the claims.
  • the claim server may also generate a survey task in the manner provided in the above embodiment, and assign the survey task to the corresponding survey personnel, and the survey personnel go to the survey.
  • the content related to the insurance accident includes a vehicle accident; after the step of performing big data analysis on the plurality of page contents to obtain the content related to the insurance accident, the method further includes: acquiring a picture of the vehicle accident, identifying the picture The license plate number; whether the license plate number is the license plate number of the insured vehicle; if so, the accident to be settled corresponding to the content related to the insurance accident is recorded.
  • the content related to the insurance accident includes a vehicle accident.
  • the claims server can obtain a picture of the vehicle accident and identify the license plate number in the picture.
  • the claim server queries whether the license plate number is the license plate number of the insured vehicle, and if so, further follows the license plate number to obtain the corresponding policy information.
  • the policy information includes the policy status and the corresponding claims terms. If the policy status is valid and the insurance accident meets the requirements of the claim clause, the claim server records the vehicle accident as a pending claim. Identifying the claims to be settled by the license plate number of the accident vehicle can effectively save the work of the survey personnel and effectively improve the recognition efficiency of the claims to be settled.
  • the claim server can then generate a survey task in the manner provided by the above embodiments to ensure that each customer who needs a claim is identified.
  • the claim server can also identify the face in the picture in the manner provided in the above embodiment, and determine whether the face is an insured client image. If so, the corresponding claims are processed according to the image of the insured customer. If there are only some people in the picture, or the person is not included in the picture, the claim server may also generate a survey task according to the manner provided in the above embodiment, and assign the survey task to the corresponding survey personnel, and the survey personnel go to the survey. This ensures that claims are provided to every customer who needs a claim.
  • an insurance accident claim processing apparatus including: a content collection module 302, a big data analysis module 304, and a claims module 306, wherein:
  • the content collection module 302 is configured to obtain a data table, where the data table includes news links of multiple websites; use the news link to access pages of multiple websites, and crawl the page content in multiple pages.
  • the big data analysis module 304 is configured to perform big data analysis on a plurality of page contents to obtain content related to an insurance accident.
  • the claim module 306 is configured to: if the claim-to-claim event is identified according to the content related to the insured event, generate a claim task according to the to-be-resolved accident, and send the claim task to the claim terminal.
  • the content collection module 302 is further configured to calculate an activity weight corresponding to the news link; scan the page according to the active weight corresponding to the news link, and if the page content is changed, update the content of the captured page. .
  • the content collection module 302 is further configured to obtain an initial weight and a time factor corresponding to the news link; scan the page corresponding to the news link according to the preset frequency, and check whether the page content is the same; if yes, the initial weight of the news link Adding the time factor, the active weight corresponding to the news link is obtained; otherwise, the initial weight of the news link is subtracted from the time factor, and the active weight corresponding to the news link is obtained.
  • the device further includes: a surveying module 308, configured to generate an accident survey task according to the content related to the insurance accident, send the accident survey task to the survey terminal, and receive the survey information returned by the survey terminal; Including customer information, the incidents to be settled corresponding to the contents related to the insurance accident are recorded.
  • a surveying module 308 configured to generate an accident survey task according to the content related to the insurance accident, send the accident survey task to the survey terminal, and receive the survey information returned by the survey terminal; Including customer information, the incidents to be settled corresponding to the contents related to the insurance accident are recorded.
  • the device further includes: a picture recognition module 310, configured to acquire a picture in the content related to the insurance accident, and identify the picture; if the face is recognized in the picture, further identify whether the face is The image of the insured customer; if so, the incident to be settled corresponding to the content related to the insured event is recorded.
  • a picture recognition module 310 configured to acquire a picture in the content related to the insurance accident, and identify the picture; if the face is recognized in the picture, further identify whether the face is The image of the insured customer; if so, the incident to be settled corresponding to the content related to the insured event is recorded.
  • the content related to the insurance accident includes a vehicle accident; the picture recognition module 310 is further configured to acquire a picture of the vehicle accident, identify the license plate number in the picture, and query whether the license plate number is the license plate number of the insured vehicle; if yes, Then record the claims to be settled corresponding to the content related to the insurance accident.
  • Each of the above-described insured claims processing devices may be implemented in whole or in part by software, hardware, and combinations thereof.
  • Each of the above modules may be embedded in or independent of the processor in the computer device, or may be stored in a memory in the computer device in a software form, so that the processor invokes the operations corresponding to the above modules.
  • a claims server is provided, as shown in FIG. 4, the claims server includes a processor coupled via a system bus, an internal memory, a non-volatile storage medium, and a network interface.
  • the processor is used to provide calculation and control capabilities.
  • the internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium.
  • An operating system and computer readable instructions are stored in the non-volatile storage medium.
  • the non-volatile storage medium can be a non-transitory computer readable storage medium.
  • the processor can be caused to perform an insurance accident claim processing method.
  • the network interface is used to communicate with an external survey terminal or claim terminal via a network connection.
  • the claim server can be implemented by a separate claims server or a claims server cluster composed of multiple claims servers.
  • a person skilled in the art can understand that the structure shown in FIG. 4 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the claims server to which the solution of the present application is applied.
  • the specific claim server may It includes more or fewer components than those shown in the figures, or some components are combined, or have different component arrangements.
  • a claim server comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor, causing the one or more processors to execute The steps of the various method embodiments above.
  • One or more non-transitory computer readable storage mediums storing computer readable instructions, when executed by one or more processors, cause one or more processors to perform the steps of the various method embodiments described above .
  • Non-volatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory can include random access memory (RAM) or external cache memory.
  • RAM is available in a variety of formats, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronization chain.
  • SRAM static RAM
  • DRAM dynamic RAM
  • SDRAM synchronous DRAM
  • DDRSDRAM double data rate SDRAM
  • ESDRAM enhanced SDRAM
  • Synchlink DRAM SLDRAM
  • Memory Bus Radbus
  • RDRAM Direct RAM
  • DRAM Direct Memory Bus Dynamic RAM
  • RDRAM Memory Bus Dynamic RAM

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Accounting & Taxation (AREA)
  • Databases & Information Systems (AREA)
  • Finance (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Development Economics (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • Technology Law (AREA)
  • General Business, Economics & Management (AREA)
  • Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)

Abstract

本申请涉及一种保险事故理赔处理方法，包括获取数据表，所述数据表中包括多个网站的新闻链接；利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容；对多种页面内容进行大数据分析，得到与保险事故相关的内容；若根据所述与保险事故相关的内容识别出待理赔事故，则根据所述待理赔事故生成理赔任务，将所述理赔任务发送至理赔终端。

Description

保险事故理赔处理方法、装置和理赔服务器
本申请要求于2017年4月11日提交中国专利局，申请号为2017102340590，申请名称为“保险事故理赔处理方法、装置和理赔服务器”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及计算机技术领域，特别是涉及一种保险事故理赔处理方法、装置和理赔服务器。
背景技术
现在社会中，保险已融入到人们的日常生活中。当客户的保险标的发生保险事故时，可以向保险公司请求理赔。在传统的方式中，保险理赔需要由客户主动发起理赔请求，保险公司根据理赔请求来进行保险理赔处理。如果客户遇到了保险事故，却没有及时提起理赔的话，很可能让客户陷入困境。如何让客户在遭遇保险事故时能够及时享受到理赔服务成为目前需要解决的一个技术问题。
发明内容
根据本申请公开的各种实施例，提供一种保险事故理赔处理方法、装置和理赔服务器。
一种保险事故理赔处理方法，包括：
获取数据表，所述数据表中包括多个网站的新闻链接；
利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容；
对多种页面内容进行大数据分析，得到与保险事故相关的内容；及
若根据所述与保险事故相关的内容识别出待理赔事故，则根据所述待理赔事故生成理赔任务，将所述理赔任务发送至理赔终端。
一种保险事故理赔处理装置，包括：
内容采集模块，用于获取数据表，所述数据表中包括多个网站的新闻链接；利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容；
大数据分析模块，用于对多种页面内容进行大数据分析，得到与保险事故相关的内容；及
理赔模块，用于若根据所述与保险事故相关的内容识别出待理赔事故，则根据所述待理赔事故生成理赔任务，将所述理赔任务发送至理赔终端。
一种理赔服务器，包括存储器和一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述处理器执行时，使得所述一个或多个处理器执行以下步骤：
获取数据表，所述数据表中包括多个网站的新闻链接；
利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容；
对多种页面内容进行大数据分析，得到与保险事故相关的内容；及
若根据所述与保险事故相关的内容识别出待理赔事故，则根据所述待理赔事故生成理赔任务，将所述理赔任务发送至理赔终端。
一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器执行以下步骤：
获取数据表，所述数据表中包括多个网站的新闻链接；
利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容；
对多种页面内容进行大数据分析，得到与保险事故相关的内容；及
若根据所述与保险事故相关的内容识别出待理赔事故，则根据所述待理赔事故生成理赔任务，将所述理赔任务发送至理赔终端。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其它的附图。
图1为根据一个或多个实施例中的保险事故理赔处理方法应用环境图；
图2为根据一个或多个实施例中保险事故理赔处理方法的流程图；
图3为根据一个或多个实施例中保险事故理赔处理装置的框图；
图4为根据一个或多个实施例中理赔服务器的框图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
本申请实施例中所提供的保险事故理赔处理方法，可以应用于如图1所示的应用环境中。理赔服务器102与多个网站服务器104通过网络建立连接。理赔服务器102与查勘终端106通过网络建立连接。理赔服务器102与理赔终端108通过网络建立连接。理赔服务器102利用爬虫技术获取多个网站服务器104的入口链接，根据入口链接获取URL列表。理赔服务器102对URL列表进行过滤，得到多个新闻链接，并且将新闻链接记录在数据表中。理赔服务器102可以按照设置的频率读取数据表中的新闻链接，利用新闻链接访问多个网站服务器提供的页面，在多个页面中抓取页面内容。理赔服务器102对于从多个网站服务器104的页面中所抓取到的页面内容进行大数据分析，得到与保险事故相关的内容。理赔服务器102获取与保险事故相关的内容中的事故基本信息，根据事故基本信息生成事故查勘任务，将查勘任务发送至查勘人员对应的查勘终端106。如果存在需要理赔的客户，则查勘终端106向理赔服务器102返回待理赔客户信息。理赔服务器102根据待理赔客户信 息记录所述与保险事故相关的内容所对应的待理赔事故。理赔服务器102根据待理赔事故生成理赔任务，将理赔任务发送至理赔终端108。理赔人员根据理赔终端接收到的理赔任务去为客户提供主动理赔服务。从而可以使得客户在遭遇保险事故时能够及时享受到理赔服务。
在一个实施例中，如图2所示，提供了一种保险事故理赔处理方法，以该方法应用于图1中的理赔服务器为例进行说明，具体包括以下步骤：
步骤202，获取数据表，数据表中包括多个网站的新闻链接。
步骤204，利用新闻链接访问多个网站的页面，在多个页面中抓取页面内容。
理赔服务器利用爬虫技术获取多个网站的入口链接，根据入口链接获取URL列表。理赔服务器对URL列表进行过滤，得到多个新闻链接。具体的，理赔服务器可以利用正则表达式对URL列表进行过滤。正则表达式采用预设格式，例如，预设格式为采用预设字符或字符串结尾的URL，如news、blog等结尾的URL。理赔服务器将多个新闻链接记录到数据表中，并且将数据表存储至数据库中。
理赔服务器可以按照设置的频率从数据库中读取该数据表。理赔服务器对数据表进行扫描，得到未曾抓取过内容的新闻链接。理赔服务器利用未曾抓取过内容的新闻链接访问多个网站的页面，在多个页面中抓取页面内容。由于理赔服务器是利用新闻链接来抓取页面内容的，因此理赔服务器采集到的页面内容具有一定的时效性。
步骤206，对新闻内容进行大数据分析，得到与保险事故相关的内容。
理赔服务器对从多个网站采集到的页面内容进行大数据分析。具体的，理赔服务器可以获取与保险相关的关键字，例如，车祸、飞机失事、地震和爆炸等。理赔服务器利用这些关键字对采集到的页面内容进行聚类分析，得到与保险事故相关的内容。例如，聚类分析可以采用K-means算法，将上述关键字依次作为数据对象通过K-means算法进行迭代计算，得到每一个关键字对应的与保险相关的内容。与保险相关的内容通常会反映一起或多起保险 事故。
理赔服务器对采集到的页面内容进行大数据分析，可以视为是对页面内容的初级筛选。理赔服务器对筛选得到的内容，即与保险相关的内容还需要做进一步的处理，以此来识别与保险相关的内容是否涉及待理赔的保险事故。识别是否存在待理赔的保险事故的方式可以包括多种。
在其中一个实施例中，理赔服务器可以获取与保险事故相关的内容中的事故基本信息，根据事故基本信息生成事故查勘任务，将查勘任务发送至查勘人员对应的查勘终端。由查勘人员去事故现场进行查勘，如果存在需要理赔的客户，则查勘终端向理赔服务器返回待理赔客户信息。理赔服务器接收到查勘终端返回的待理赔客户信息，根据待理赔客户信息记录与保险事故相关的内容所对应的待理赔事故。
在其中一个实施例中，理赔服务器可以获取与保险事故相关的内容的图片，识别图片中是否有人脸，若有，则进一步识别该人脸是否为被保险的客户图像。若是，则理赔服务器根据客户图像记录与保险事故相关的内容所对应的待理赔事故。
如果与保险事故相关的内容包括车辆事故，在其中一个实施例中，理赔服务器还可以在车辆事故的图片中识别相应的车牌号。如果识别出的车牌号码为被保险车辆的车牌号，则理赔服务器根据车牌号记录与保险事故相关的内容所对应的待理赔事故。
步骤208，若根据与保险事故相关的内容识别出待理赔事故，则根据待理赔事故生成理赔任务，将理赔任务发送至理赔终端。
如果根据保险事故相关的内容识别出存在待理赔事故，那么理赔服务器可以根据待理赔事故获取对应的客户信息，根据客户信息在数据库中提取对应的保单信息。理赔服务器根据保单信息和待理赔事故生成理赔任务，将理赔任务发送至理赔终端。理赔人员根据理赔终端接收到的理赔任务去为客户提供主动理赔服务。从而可以使得客户在遭遇保险事故时能够及时享受到理赔服务。
本实施例中，通过利用多个网站的新闻链接在多个网站的页面中抓取页面内容。对多种页面内容进行大数据分析，可以得到与保险事故相关的内容。由此能够及时的获取到当前与保险事故相关的内容。如果根据与保险相关的内容识别出待理赔事故，则可以根据待理赔事故生成理赔任务，将理赔任务发送至理赔终端。理赔人员根据理赔终端接收到的理赔任务去为客户提供主动理赔服务。从而可以使得客户在遭遇保险事故时能够及时享受到理赔服务。
应该理解的是，虽然图2的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，图2中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
在一个实施例中，在利用新闻链接访问多个网站的页面，在多个页面中抓取页面内容的步骤之后，还包括：计算新闻链接对应的活跃权重；根据新闻链接对应的活跃权重对页面进行扫描，若发现页面内容有变化，则对已经抓取的页面内容进行更新。
随着时间的推移，页面内容可能会发生变化。页面内容变化越快，表示相应的新闻链接越活跃。以页面内容为论坛中的帖子为例，如果页面内容反映了热点事件，相应的新闻链接会较为活跃，在帖子发布后的当天以及之后几天通常会有较多回帖。为了能够采集到更丰富的页面内容，理赔服务器不仅需要抓取帖子的内容，还需要抓取回帖的内容。
本实施例中，新闻链接的活跃度可以通过活跃权重来反映。理赔服务器在利用多个新闻链接从多个网站抓取到页面内容之后，还会计算每个新闻链接对应的活跃权重。同一新闻链接的活跃度在不同的时间可以是不同的，不同新闻链接的活跃度在不同时间也可以是各不相同的。服务器可以利用新闻 链接对应的初始权重与时间因子计算新闻链接的活跃权重。数据表中每个新闻链接的初始权重可以相同，也可以不同。时间因子可以相同，也可以不同。
在其中一个实施例中，计算新闻链接对应的活跃权重的步骤，包括：获取新闻链接对应的初始权重和时间因子；按照预设频率扫描新闻链接对应的页面，查看页面内容是否相同；若是，则将新闻链接的初始权重加上时间因子，得到新闻链接对应的活跃权重；否则，将新闻链接的初始权重减去时间因子，得到新闻链接对应的活跃权重。
理赔服务器可以为数据表中的每个新闻链接配置相应的初始权重和时间因子。理赔服务器可以按照设置的频率扫描每个新闻链接对应的页面，查看页面内容是否相同。如果相同，则表示页面内容没有发生变化，理赔服务器可以减少对该新闻链接的访问频次。理赔服务器将该新闻链接的初始权重加上时间因子，由此计算出该新闻链接对应的活跃权重。如果理赔服务器扫描新闻链接对应的页面后，发现页面内容与上一次抓取到的内容不同，则表示页面内容发生了变化。理赔服务器可以提高对该新闻链接的访问频次。理赔服务器将该新闻链接的初始权重减去时间因子，得到该新闻链接对应的活跃权重。
活跃权重可以反映新闻链接的活跃度。其中，活跃权重越低表示新闻链接的活跃度越高，活跃权重越高表示新闻链接的活跃度越低。例如，理赔服务器对新闻链接配置的初始权重均为1，时间因子均为0.4。理赔服务器可以按照1天/次的频率来扫描每个新闻链接对应的页面。如果某个新闻链接对应的页面内容没有发生变化，则理赔服务器计算其对应的活跃权重为1+0.4＝1.4。这表示理赔服务器将在1.4天之后再次扫描该新闻链接所对应的页面。如果某个新闻链接对应的页面内容发生了变化，则理赔服务器计算其对应的活跃权重为1-0.4＝0.6。这表示理赔服务器将在0.6天之后再次扫描该新闻链接所对应的页面。
理赔服务器根据新闻链接对应的活跃权重对页面进行扫描，如果扫描后发现页面内容依旧没有发生变化，则理赔服务器将其当前的活跃权重加上时 间因子，计算得到下一次访问该新闻链接对应页面的活跃权重。以此类推，当计算出的活跃权重大于或等于第一预算值后，则表示该新闻链接对应的页面已经不再活跃，可以不需要再扫描该页面的内容。理赔服务器不再继续计算该新闻链接对应的活跃权重。
如果扫描后发现页面内容再次发生变化，则理赔服务器将其当前的活跃权重减去时间因子，计算得到下一次访问该新闻链接对应页面的活跃权重。以此类推，当计算出的活跃权重小于或等于第二预设值后，则表示该新闻链接对应的页面较为活跃，为了有效节省理赔服务器资源，理赔服务器可以不再继续计算下一次访问该新闻链接对应页面的活跃权重，可以直接将第二预设值作为该新闻链接对应的活跃权重。
如果理赔服务器按照第二预设值作为新闻链接对应的活跃权重对页面进行扫描时，发现其内容的变化时间延长，则理赔服务器可以按照上面提供的方法将第二预设值加上时间因子，计算下一次访问该新闻链接对应页面的活跃权重，直至其活跃权重大于或等于第一预设值。
理赔服务器根据新闻链接对应的活跃权重对页面进行扫描，如果发现页面内容有变化，则抓取该页面的内容，或者仅抓取该页面上发生变化的内容，通过抓取到的内容对已经抓取的页面内容进行更新。例如，更新的内容可以是评论，也可以是帖子回复，如果更新的内容中包括与事故中的人物、或地址相关的内容，则可以有助于快速识别出一起保险事故。通过对抓取的页面内容进行更新，可以为大数据分析与保险事故相关的内容提供辅助帮助。
在一个实施例中，在对多种页面内容进行大数据分析，得到与保险事故相关的内容的步骤之后，还包括：在与保险事故相关的内容中获取图片，对图片进行识别；若在图片中识别出人脸，则进一步识别人脸是否为被保险的客户图像；若是，则记录与保险事故相关的内容所对应的待理赔事故。
本实施例中，理赔服务器可以根据大数据分析的结果，获取与保险事故相关的内容中的事故基本信息。事故基本信息包括事故时间、事故地点以及事故类型等。理赔服务器可以根据事故基本信息生成事故查勘任务，将查勘 任务发送至查勘人员对应的查勘终端。具体的，理赔服务器可以根据事故地点获取相应区域范围内的查勘人员标识，根据查勘人员标识与事故类型，查询熟悉该事故类型的查勘人员标识。理赔服务器将查勘任务发送至该查勘人员标识对应的查勘终端。由此可以使得熟悉该事故类型的查勘人员能够及时去进行查勘，以便识别本次事故中是否存在需要理赔的客户。如果存在需要理赔的客户，则查勘人员通过查勘终端输入待理赔客户信息，查勘终端将待理赔客户信息上传至理赔服务器。理赔服务器接收到待理赔客户信息之后，根据待理赔客户信息获取对应的保单信息。保单信息包括保单状态以及对应的理赔条款。如果保单状态为有效并且本次保险事故符合理赔条款的规定，则理赔服务器记录与保险事故相关的内容所对应的待理赔事故。由此可以准确识别出待理赔事故。由于一起保险事故中可能会涉及到一个或多个待理赔客户，因此通过分配查勘任务的方式让查勘人员前去查勘，能够准确识别出每一个需要理赔的客户。从而确保能够为每一个遭遇保险事故的客户提供及时有效的理赔服务。
在一个实施例，在对多种页面内容进行大数据分析，得到与保险事故相关的内容的步骤之后，还包括：在与保险事故相关的内容中获取图片，对图片进行识别；若在图片中识别出人脸，则进一步识别人脸是否为被保险的客户图像；若是，则根据客户图像获取客户信息，记录与保险事故相关的内容所对应的待理赔事故。
本实施例中，在大数据分析的结果中，与保险事故相关的内容中可以包括图片。理赔服务器提取保险事故的图片，对图片进行识别。如果在图片中识别出人脸，则进一步判断该人脸是否为被保险的客户图像。理赔服务器的数据库中存储了大量的被保险的客户图像。被保险的客户图像可以对应一份或多份保单。理赔服务器可以将识别出的人脸图像与数据库中存储的客户图像进行匹配，若与数据库中某一个客户图像的匹配值超过阈值，则将从图片中识别出的人脸图像记录为被保险的客户图像。
理赔服务器在识别出被保险的客户图像之后，根据客户图像获取客户信 息以及对应的保单信息。保单信息包括保单状态以及对应的理赔条款。如果保单状态为有效并且本次保险事故符合理赔条款的规定，则理赔服务器根据客户信息记录与保险事故相关的内容所对应的待理赔事故。由此可以准确识别出待理赔事故。通过人脸识别匹配的方式识别出待理赔事故，能够有效节省查勘人员的工作，并且能够有效提高待理赔事故的识别效率。
进一步的，如果本次保险事故中涉及到的人员较多，虽然能够从图片中识别出部分待理赔事故，为了确保能够为每一位需要理赔的客户及时提供理赔服务。理赔服务器还可以按照上述实施例中提供的方式生成查勘任务，并且将查勘任务分配至对应的查勘人员，由查勘人员前去查勘。
在一个实施例中，与保险事故相关的内容包括车辆事故；在对多种页面内容进行大数据分析，得到与保险事故相关的内容的步骤之后，还包括：获取车辆事故的图片，识别图片中的车牌号；查询车牌号是否为被保险车辆的车牌号；若是，则记录与保险事故相关的内容所对应的待理赔事故。
本实施例中，与保险事故相关的内容包括车辆事故。对于大数据分析结果中的车辆事故，理赔服务器可以获取车辆事故的图片，识别所述图片中的车牌号。理赔服务器查询该车牌号是否为被保险车辆的车牌号，如果是，则进一步跟进车牌号获取对应的保单信息。保单信息包括保单状态以及对应的理赔条款。如果保单状态为有效并且本次保险事故符合理赔条款的规定，则理赔服务器记录本次车辆事故为待理赔事故。通过事故车辆的车牌号来识别出待理赔事故，能够有效节省查勘人员的工作，并且能够有效提高待理赔事故的识别效率。
进一步的，如果本次车辆事故中涉及到的事故车辆较多，且有部分事故车辆的车牌号未能出现在图片中。则理赔服务器可以按照上述实施例提供的方式生成查勘任务，以确保识别出每一个需要理赔的客户。
进一步的，如果本次车辆事故中不仅涉及到车辆，还涉及到人员。理赔服务器还可以按照上述实施例中提供的方式来识别图片中的人脸，判断该人脸是否为被保险客户图像。若是，根据被保险客户图像记录相应的待理赔事 故。如果图片中仅有部分人员，或者图片中不包括人员，则理赔服务器还可以按照上述实施例中提供的方式生成查勘任务，并且将查勘任务分配至对应的查勘人员，由查勘人员前去查勘。以此确保为每一位需要理赔的客户及时提供理赔服务。
在一个实施例中，如图3所示，提供了一种保险事故理赔处理装置，包括：内容采集模块302、大数据分析模块304和理赔模块306，其中：
内容采集模块302，用于获取数据表，数据表中包括多个网站的新闻链接；利用新闻链接访问多个网站的页面，在多个页面中抓取页面内容。
大数据分析模块304，用于对多种页面内容进行大数据分析，得到与保险事故相关的内容。
理赔模块306，用于若根据与保险事故相关的内容识别出待理赔事故，则根据待理赔事故生成理赔任务，将理赔任务发送至理赔终端。
在一个实施例中，内容采集模块302还用于计算新闻链接对应的活跃权重；根据新闻链接对应的活跃权重对页面进行扫描，若发现页面内容有变化，则对已经抓取的页面内容进行更新。
在一个实施例中，内容采集模块302还用于获取新闻链接对应的初始权重和时间因子；按照预设频率扫描新闻链接对应的页面，查看页面内容是否相同；若是，则将新闻链接的初始权重加上时间因子，得到新闻链接对应的活跃权重；否则，将新闻链接的初始权重减去时间因子，得到新闻链接对应的活跃权重。
在一个实施例中，该装置还包括：查勘模块308，用于根据与保险事故相关的内容生成事故查勘任务，将事故查勘任务发送至查勘终端；接收查勘终端返回的查勘信息；若查勘信息中包括客户信息，则记录与保险事故相关的内容所对应的待理赔事故。
在一个实施例中，该装置还包括：图片识别模块310，用于在与保险事故相关的内容中获取图片，对图片进行识别；若在图片中识别出人脸，则进一步识别人脸是否为被保险的客户图像；若是，则记录与保险事故相关的内 容所对应的待理赔事故。
在一个实施例中，与保险事故相关的内容包括车辆事故；图片识别模块310还用于获取车辆事故的图片，识别图片中的车牌号；查询车牌号是否为被保险车辆的车牌号；若是，则记录与保险事故相关的内容所对应的待理赔事故。
关于保险事故理赔处理装置的具体限定可以参见上文中对于保险事故理赔处理方法的限定，在此不再赘述。上述保险事故理赔处理装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在一个实施例中，提供了一种理赔服务器，如图4所示，该理赔服务器包括通过系统总线连接的处理器、内存储器、非易失性存储介质和网络接口。其中，处理器用于提供计算和控制能力。内存储器为非易失性存储介质中的操作系统和计算机程序的运行提供环境。非易失性存储介质中存储有操作系统和计算机可读指令。非易失性存储介质可以是非易失性计算机可读存储介质。计算机可读指令被处理器执行时，可使得处理器执行一种保险事故理赔处理方法。网络接口用于据以与外部的查勘终端或理赔终端通过网络连接通信。该理赔服务器可以用独立的理赔服务器或者是多个理赔服务器组成的理赔服务器集群来实现。本领域技术人员可以理解，图4中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的理赔服务器的限定，具体的理赔服务器可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
一种理赔服务器，包括存储器和一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述处理器执行时，使得所述一个或多个处理器执行上述各个方法实施例的步骤。
一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器执行上述 各个方法实施例的步骤。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机可读指令来指令相关的硬件来完成，所述的计算机可读指令可存储于一非易失性计算机可读取存储介质中，该计算机可读指令在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (20)

  1. 一种保险事故理赔处理方法，包括：
    获取数据表，所述数据表中包括多个网站的新闻链接；
    利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容；
    对多种页面内容进行大数据分析，得到与保险事故相关的内容；及
    若根据所述与保险事故相关的内容识别出待理赔事故，则根据所述待理赔事故生成理赔任务，将所述理赔任务发送至理赔终端。
  2. 根据权利要求1所述的方法，其特征在于，在所述利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容之后，还包括：
    计算所述新闻链接对应的活跃权重；及
    根据所述新闻链接对应的活跃权重对页面进行扫描，若发现页面内容有变化，则对已经抓取的页面内容进行更新。
  3. 根据权利要求2所述的方法，其特征在于，所述计算所述新闻链接对应的活跃权重包括：
    获取所述新闻链接对应的初始权重和时间因子；
    按照预设频率扫描所述新闻链接对应的页面，查看页面内容是否相同；
    若是，则将所述新闻链接的初始权重加上时间因子，得到所述新闻链接对应的活跃权重；及
    否则，将所述新闻链接的初始权重减去时间因子，得到所述新闻链接对应的活跃权重。
  4. 根据权利要求1所述的方法，其特征在于，在所述对多种页面内容进行大数据分析，得到与保险事故相关的内容之后，还包括：
    根据所述与保险事故相关的内容生成事故查勘任务，将所述事故查勘任务发送至查勘终端；
    接收查勘终端返回的查勘信息；及
    若所述查勘信息中包括客户信息，则记录所述与保险事故相关的内容所对应的待理赔事故。
  5. 根据权利要求1所述的方法，其特征在于，在所述对多种页面内容进行大数据分析，得到与保险事故相关的内容之后，还包括：
    在所述与保险事故相关的内容中获取图片，对所述图片进行识别；
    若在所述图片中识别出人脸，则进一步识别所述人脸是否为被保险的客户图像；及
    若是，则记录所述与保险事故相关的内容所对应的待理赔事故。
  6. 根据权利要求1所述的方法，其特征在于，所述与保险事故相关的内容包括车辆事故；在所述对多种页面内容进行大数据分析，得到与保险事故相关的内容之后，还包括：
    获取所述车辆事故的图片，识别所述图片中的车牌号；
    查询所述车牌号是否为被保险车辆的车牌号；及
    若是，则记录所述与保险事故相关的内容所对应的待理赔事故。
  7. 一种保险事故理赔处理装置，包括：
    内容采集模块，用于获取数据表，所述数据表中包括多个网站的新闻链接；利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容；
    大数据分析模块，用于对多种页面内容进行大数据分析，得到与保险事故相关的内容；及
    理赔模块，用于若根据所述与保险事故相关的内容识别出待理赔事故，则根据所述待理赔事故生成理赔任务，将所述理赔任务发送至理赔终端。
  8. 根据权利要求7所述的装置，其特征在于，所述内容采集模块还用于计算所述新闻链接对应的活跃权重；及根据所述新闻链接对应的活跃权重对页面进行扫描，若发现页面内容有变化，则对已经抓取的页面内容进行更新。
  9. 根据权利要求8所述的装置，其特征在于，所述内容采集模块还用于获取所述新闻链接对应的初始权重和时间因子；按照预设频率扫描所述新闻链接对应的页面，查看页面内容是否相同；若是，则将所述新闻链接的初始权重加上时间因子，得到所述新闻链接对应的活跃权重；及否则，将所述新 闻链接的初始权重减去时间因子，得到所述新闻链接对应的活跃权重。
  10. 一种理赔服务器，包括存储器和一个或多个处理器，存储器中储存有计算机可读指令，计算机可读指令被处理器执行时，使得一个或多个处理器执行以下步骤：
    获取数据表，所述数据表中包括多个网站的新闻链接；
    利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容；
    对多种页面内容进行大数据分析，得到与保险事故相关的内容；及
    若根据所述与保险事故相关的内容识别出待理赔事故，则根据所述待理赔事故生成理赔任务，将所述理赔任务发送至理赔终端。
  11. 根据权利要求10所述的理赔服务器，其特征在于，所述计算机可读指令被处理器执行时，使得一个或多个处理器还执行以下步骤：
    计算所述新闻链接对应的活跃权重；及
    根据所述新闻链接对应的活跃权重对页面进行扫描，若发现页面内容有变化，则对已经抓取的页面内容进行更新。
  12. 根据权利要求11理赔服务器，其特征在于，所述计算机可读指令被处理器执行时，使得一个或多个处理器还执行以下步骤：
    获取所述新闻链接对应的初始权重和时间因子；
    按照预设频率扫描所述新闻链接对应的页面，查看页面内容是否相同；
    若是，则将所述新闻链接的初始权重加上时间因子，得到所述新闻链接对应的活跃权重；及
    否则，将所述新闻链接的初始权重减去时间因子，得到所述新闻链接对应的活跃权重。
  13. 根据权利要求10所述的理赔服务器，其特征在于，所述计算机可读指令被处理器执行时，使得一个或多个处理器还执行以下步骤：
    根据所述与保险事故相关的内容生成事故查勘任务，将所述事故查勘任务发送至查勘终端；
    接收查勘终端返回的查勘信息；及
    若所述查勘信息中包括客户信息，则记录所述与保险事故相关的内容所对应的待理赔事故。
  14. 根据权利要求10所述的理赔服务器，其特征在于，所述计算机可读指令被处理器执行时，使得一个或多个处理器还执行以下步骤：
    在所述与保险事故相关的内容中获取图片，对所述图片进行识别；
    若在所述图片中识别出人脸，则进一步识别所述人脸是否为被保险的客户图像；及
    若是，则记录所述与保险事故相关的内容所对应的待理赔事故。
  15. 根据权利要求10所述的理赔服务器，其特征在于，所述与保险事故相关的内容包括车辆事故；所述计算机可读指令被处理器执行时，使得一个或多个处理器还执行以下步骤：
    获取所述车辆事故的图片，识别所述图片中的车牌号；
    查询所述车牌号是否为被保险车辆的车牌号；及
    若是，则记录所述与保险事故相关的内容所对应的待理赔事故。
  16. 一个或多个存储有计算机可读指令的非易失性存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器执行以下步骤：
    获取数据表，所述数据表中包括多个网站的新闻链接；
    利用所述新闻链接访问多个网站的页面，在多个页面中抓取页面内容；
    对多种页面内容进行大数据分析，得到与保险事故相关的内容；及
    若根据所述与保险事故相关的内容识别出待理赔事故，则根据所述待理赔事故生成理赔任务，将所述理赔任务发送至理赔终端。
  17. 根据权利要求16所述的存储介质，其特征在于，所述计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器还执行以下步骤：
    计算所述新闻链接对应的活跃权重；及
    根据所述新闻链接对应的活跃权重对页面进行扫描，若发现页面内容有变化，则对已经抓取的页面内容进行更新。
  18. 根据权利要求17所述的存储介质，其特征在于，所述计算机可读指 令被一个或多个处理器执行时，使得一个或多个处理器还执行以下步骤：
    获取所述新闻链接对应的初始权重和时间因子；
    按照预设频率扫描所述新闻链接对应的页面，查看页面内容是否相同；
    若是，则将所述新闻链接的初始权重加上时间因子，得到所述新闻链接对应的活跃权重；及
    否则，将所述新闻链接的初始权重减去时间因子，得到所述新闻链接对应的活跃权重。
  19. 根据权利要求17所述的存储介质，其特征在于，所述计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器还执行以下步骤：
    根据所述与保险事故相关的内容生成事故查勘任务，将所述事故查勘任务发送至查勘终端；
    接收查勘终端返回的查勘信息；及
    若所述查勘信息中包括客户信息，则记录所述与保险事故相关的内容所对应的待理赔事故。
  20. 根据权利要求17所述的存储介质，其特征在于，所述计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器还执行以下步骤：
    在所述与保险事故相关的内容中获取图片，对所述图片进行识别；
    若在所述图片中识别出人脸，则进一步识别所述人脸是否为被保险的客户图像；及
    若是，则记录所述与保险事故相关的内容所对应的待理赔事故。
PCT/CN2018/082286 2017-04-11 2018-04-09 保险事故理赔处理方法、装置和理赔服务器 Ceased WO2018188545A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201710234059.0A CN108255902B (zh) 2017-04-11 2017-04-11 保险事故理赔处理方法、装置和理赔服务器
CN201710234059.0 2017-04-11

Publications (1)

Publication Number Publication Date
WO2018188545A1 true WO2018188545A1 (zh) 2018-10-18

Family

ID=62721797

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/082286 Ceased WO2018188545A1 (zh) 2017-04-11 2018-04-09 保险事故理赔处理方法、装置和理赔服务器

Country Status (2)

Country Link
CN (1) CN108255902B (zh)
WO (1) WO2018188545A1 (zh)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI676954B (zh) * 2018-08-31 2019-11-11 新光產物保險股份有限公司 自動理賠系統及其方法
CN110992214B (zh) * 2019-11-29 2022-08-16 成都中科大旗软件股份有限公司 一种基于旅游名县和示范区的服务管理系统和方法
CN111461903A (zh) * 2020-04-14 2020-07-28 诺映(上海)信息科技有限公司 商业健康保险线上无单证主动理赔技术
CN113436025B (zh) * 2021-05-18 2023-06-27 臻顺溜科技股份有限公司 非标准保单的投保系统及投保方法

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104182916A (zh) * 2014-08-31 2014-12-03 上海报春通信科技有限公司 一种航班延误保险的主动理赔服务系统
US20170039656A1 (en) * 2013-06-25 2017-02-09 Arthur Paul Drennan, III System and method for evaluating text to support multiple insurance applications
CN106504173A (zh) * 2016-12-19 2017-03-15 东软集团股份有限公司 交通事故处理的方法、装置及系统
CN107180389A (zh) * 2017-05-10 2017-09-19 平安科技（深圳）有限公司 人伤理赔定损费用测算方法、装置、服务器和介质
CN107886437A (zh) * 2017-11-09 2018-04-06 中国平安财产保险股份有限公司 主动查勘处理方法、系统、计算机设备和存储介质

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3493154B2 (ja) * 1999-01-29 2004-02-03 富士通株式会社 営業支援システムおよび記録媒体
CN104615727A (zh) * 2015-02-09 2015-05-13 杭州中导科技开发有限公司 一种获取保险关联信息的方法
CN106228448A (zh) * 2016-07-29 2016-12-14 深圳市永兴元科技有限公司 基于移动通信网络的车险理赔方法及装置

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170039656A1 (en) * 2013-06-25 2017-02-09 Arthur Paul Drennan, III System and method for evaluating text to support multiple insurance applications
CN104182916A (zh) * 2014-08-31 2014-12-03 上海报春通信科技有限公司 一种航班延误保险的主动理赔服务系统
CN106504173A (zh) * 2016-12-19 2017-03-15 东软集团股份有限公司 交通事故处理的方法、装置及系统
CN107180389A (zh) * 2017-05-10 2017-09-19 平安科技（深圳）有限公司 人伤理赔定损费用测算方法、装置、服务器和介质
CN107886437A (zh) * 2017-11-09 2018-04-06 中国平安财产保险股份有限公司 主动查勘处理方法、系统、计算机设备和存储介质

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
HUANG, YUE ET AL.: "Big Data Meets the Needs of Disaster Information Management", JOURNAL OF NANJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS (NATURAL SCIENCE), 31 December 2015 (2015-12-31), pages 72 - 73 *

Also Published As

Publication number Publication date
CN108255902A (zh) 2018-07-06
CN108255902B (zh) 2021-01-12

Similar Documents

Publication Publication Date Title
US11797519B2 (en) Atomic capture of a set of related files, using a distributed ledger, for proof of authenticity
van Baar et al. Digital forensics as a service: A game changer
US9158843B1 (en) Addressing mechanism for data at world wide scale
WO2021135323A1 (zh) 城市多源异构数据的融合处理方法、装置和计算机设备
US8949330B2 (en) Systems and methods for automated recommendations for social media
US11416631B2 (en) Dynamic monitoring of movement of data
CN110990390B (zh) 数据协同处理方法、装置、计算机设备和存储介质
Quick et al. Big forensic data management in heterogeneous distributed systems: quick analysis of multimedia forensic data
WO2018188545A1 (zh) 保险事故理赔处理方法、装置和理赔服务器
CN103888490A (zh) 一种全自动的web客户端人机识别的方法
US10303393B2 (en) Technology for governance of data retention and transfer
US12468983B2 (en) Machine Learning (ML) model pipeline with obfuscation to protect sensitive data therein
US10462257B2 (en) Method and apparatus for obtaining user account
US20220335154A1 (en) Predictive response-generation systems to facilitate timely compliance with information-disclosure laws
US8756292B2 (en) Smart cache learning mechanism in enterprise portal navigation
CN109542764B (zh) 网页自动化测试方法、装置、计算机设备和存储介质
US20210049267A1 (en) Automated dynamic security testing
US12395512B2 (en) Detecting data exfiltration and compromised user accounts in a computing network
CN110619075B (zh) 一种网页识别方法与设备
CN112508720A (zh) 保险客户身份属性的筛选方法、筛选装置及电子设备
US20210165911A1 (en) System and method for improving security of personally identifiable information
CN107193834A (zh) 用于浏览页面的计算设备、装置及方法
CN110276028B (zh) 针对业务系统的内部链路功能需求的处理方法和装置
US20180295145A1 (en) Multicomputer Digital Data Processing to Provide Information Security Control
CN109302406B (zh) 一种分布式网页取证的方法及系统

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18784554

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 15/01/2020)

122 Ep: pct application non-entry in european phase

Ref document number: 18784554

Country of ref document: EP

Kind code of ref document: A1