CN106599143B - High-speed information retrieval method - Google Patents
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- CN106599143B CN106599143B CN201611109223.7A CN201611109223A CN106599143B CN 106599143 B CN106599143 B CN 106599143B CN 201611109223 A CN201611109223 A CN 201611109223A CN 106599143 B CN106599143 B CN 106599143B
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Abstract
A high-speed information retrieval method includes the steps of: a user inputs and sends a search request from a client; the receiving end carries out security authentication on the received search request; if the search request passes the authentication, the type of the search request is judged, and then the search request is further input into a search processing module; if not, sending a search response containing rejection information to the client; the search processing module carries out high-speed search; and displaying the search results in sequence from high to low according to the degree of correlation. The method can improve the searching speed and efficiency, improve the precision ratio and the recall ratio, eliminate improper searching requests in advance to reduce the searching time, reduce unnecessary occupation of resources of a receiving end, further increase the workload and energy consumption of the receiving end, and reduce the data scheduling efficiency and speed of the receiving end.
Description
Technical Field
The invention relates to the field of electric digital data processing, in particular to a high-speed information retrieval method.
Background
With the continuous improvement of social industrialization and informatization levels, data replaces calculation to become a center of information calculation, and the internet, cloud calculation and big data are becoming a trend and trend. Nowadays, the internet has become the most important way for people to obtain information, and a great deal of valuable information and knowledge are hidden in network resources. However, the explosive growth of network resources may be called prosperity and consummation, which brings more and more abundant information to users, and at the same time, the difficulty of obtaining relevant knowledge precisely required by users is increasing. In addition, due to the diversification of user expressions, different expressions exist in the same term, or different expressions with the same or similar meanings exist, and how to quickly and efficiently extract useful information from a large amount of network information becomes the most important task in information search nowadays.
In the prior art, there are several search engines in an attempt to solve these problems, such as hundredths, google, dog search, etc. As an important tool for information search, the information search method and the information search device become a main way for users to experience the Internet and obtain information, and people can obtain required information on the Internet conveniently. The traditional network information searching mode is as follows: initializing a uniform resource locator, grabbing a webpage through a crawler, arranging the webpage after grabbing the uniform resource locator in a waiting queue for gathering, judging whether a condition is met, stopping if the condition is met, and otherwise, repeatedly executing. However, as the content of web pages is becoming rich and the topics of web pages are becoming diversified, the disadvantages and limitations of search engines are becoming increasingly apparent. The main problems are that the commercial advertisement is too much, the speed is still to be improved, the precision ratio and the recall ratio are not high enough, the associative search is lacked, and the like. For example, after a long-time search, information about a panda that is an animal is required to be known, such as panda tv, panda cigarette, panda stationery, and the like, which are not all really required by a user, but are not extended to information about a panda and the like, and it takes a long time to discriminate. Therefore, a high-speed information search method and device are urgently needed, which can improve the search speed and efficiency and can also improve the precision ratio and the recall ratio.
Disclosure of Invention
An object of the present invention is to provide a high-speed information retrieval method and system, which can improve the search speed and efficiency, and also improve the precision ratio and the recall ratio, and can eliminate the improper search request in advance to reduce the search time, reduce the unnecessary occupation of the resources of the receiving end, further increase the workload and energy consumption of the receiving end, and reduce the data scheduling efficiency and speed of the receiving end.
The technical scheme adopted by the invention to solve the technical problems is as follows: a high-speed information retrieval method, comprising: a user inputs and sends a search request from a client; the receiving end carries out security authentication on the received search request; if the search request passes the authentication, the type of the search request is judged, and then the search request is further input into a search processing module; if not, sending a search response containing rejection information to the client; the search processing module carries out high-speed search; and displaying the search results in sequence from high to low according to the degree of correlation.
According to another aspect of the present invention, in step S2, the receiving end performing security authentication on the received search request further includes: the client that sends the search request to the receiver is authenticated, including the security of the client's search request, the eligibility to authorize access to the receiver, and the legitimacy of the search request content.
According to another aspect of the present invention, the making a type decision on the search request in step S3 further comprises: the search request is sent to a type judging device, and the type judging device judges the type of the search request, wherein the type at least comprises characters such as characters, numbers and the like, voice, static pictures, videos, code segments and application programs.
According to another aspect of the present invention, in the step S3, the step S31 is further included after the step S3 of inputting into the search processing module: a comparison step; the comparing step of step S31 further includes: step S311, the search processing module compares the search request with the search records of the same type in the search record list stored on the search processing module according to the judged type of the search request, and judges the correlation degree of the search request and the search records; in step S312, if the correlation between the two records exceeds the first threshold, the destination record of the search record whose correlation exceeds the first threshold is retrieved from the search record list stored in the search processing module, and the location in the big data environment linked to the destination record is mapped, and the associated content of the location is retrieved and returned to the search processing module; the search processing module encrypts data according to needs to form a search packet and sends the search packet to a receiving end; in step S313, if the correlation between the two does not exceed the first threshold, the search processing module performs a subsequent search.
According to another aspect of the present invention, after the step S3, the method further comprises the step S32: dividing the search request S after determining the search request type into one or more sub-requests SiI is a positive integer, where s is the smallest searchable unit when the search request isiIs one, otherwise is a plurality, where S ═ { S ═ S1，……，si，……，sPAnd P is the number of the sub-requests and is a positive integer.
According to another aspect of the present invention, after the step S3, the method further comprises the step S33: based on sub-request siThe semantic processing module is used for effectively expanding; the step S33 of performing effective expansion by the semantic processing module further includes: step S331: first module of semantic processing module analyzes sub-request siDetermining semantics of the user request, and associating the semantics with the determined concept or object; step S332, the semantic processing module sends a call request to the synonym/near-synonym semantic database, wherein the call request includes a sub-request SiThe information of (a); step S333, returning a calling result after traversing the synonym/near-synonym meaning database to serve as a calling response; in step S334, the semantic processing module receives the call response and sends the call response to the search processing module.
According to another aspect of the invention, the semantic processing module sends the sub-request s through a second module of the semantic processing module after receiving the call response and before sending it to the search processing moduleiAnd expanding the words by using a plurality of language expression modes, packaging the words and the call response sent by the synonym/near-synonym meaning database and sending the words and the call response to the search processing module.
According to another aspect of the present invention, the step S5 further includes: step S51, the search processing module instructs the extraction module to extract the characteristics of the unit source data; step S52, the search processing module traverses the extracted features of the unit source data based on the call response, performs correlation matching between the call response and the extracted features of the unit source data, and records the matching frequency according to different parts of the unit source data; step S53, if the matching condition is satisfied, the matching event is sent to the event processing module; in step S54, the search processing module traverses all the source data and sends each matching event to the event processing module.
According to another aspect of the present invention, in step S6, the method further comprises: in step S61, the event processing module counts the total matching metric, i.e. the degree of correlation, M of the individual source data according to the received event and the recorded matching frequency of different parts of the unit source dataijWherein
Where Q is the total number of different portions of the unit source data, mjDenotes the number of matches in the jth part of the unit source data, and wjA weight representing a jth part of the unit source data; step S62, the event processing module carries out statistic ordering according to each unit data source; in step S63, the search results are displayed in order from high to low according to the degree of correlation.
According to another aspect of the present invention, there is also provided a high-speed information retrieval system for performing the high-speed information retrieval method.
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Embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:
fig. 1 illustrates a high-speed information search method according to an exemplary embodiment of the present invention.
Detailed Description
In the following description, reference is made to the accompanying drawings that show, by way of illustration, several specific embodiments. It will be understood that: other embodiments are contemplated and may be made without departing from the scope or spirit of the present disclosure. The following detailed description is, therefore, not to be taken in a limiting sense.
Fig. 1 illustrates a high-speed information search method according to an exemplary embodiment of the present invention. The method comprises the following steps:
in step S1, the user inputs and sends a search request from the client;
in step S2, the receiving end performs security authentication on the received search request;
in step S3, if the authentication is passed, the search request is subjected to type determination, and then further input into the search processing module;
in step S4, if not, sending a search response containing rejection information to the client;
in step S5, the search processing module performs a high-speed search; and
in step S6, the search results are displayed in order from high to low according to the degree of correlation.
In step S2, the receiving end performing security authentication on the received search request further includes: authenticating a client that sends a search request to a recipient may include, for example and without limitation, security of the client's search request, eligibility to authorize access to the recipient, legitimacy of the search request content, and so forth. Due to the diversity of the types of search requests, not only characters such as characters and numbers (i.e. traditional search) can be input, but also voices (e.g. inputting recorded bird call to search for the name and associated information of the corresponding bird), pictures (e.g. inputting photos of scarabs, and then searching for a corresponding series of associated information), videos (including short films downloaded by the user through an instant messaging tool), and applications (including applets, apps, program fragments, etc.) can be input. However, for example, if the input program contains malicious software or code, the security of the receiving end is affected, and in order to avoid threatening the security of the whole receiving end, the security of the client search request of the client must be authenticated. In addition, sometimes, the information of the receiving end may be charged due to intellectual property, so the authentication must include the qualification of authorizing access to the receiving end, and if the receiving end is not authorized to be accessed, the search request is directly rejected to be excluded in advance to reduce the search time, reduce unnecessary occupation of resources of the receiving end, further increase the workload and energy consumption of the receiving end, and reduce the data scheduling efficiency and speed of the receiving end. In addition, sometimes, since some countries and regions have different legal and ethical requirements and need to filter some illegal search requests, the authentication may also include legitimacy authentication of search request contents to eliminate in advance to reduce search time and reduce unnecessary occupation of resources of the receiving end, thereby increasing workload and energy consumption of the receiving end and reducing data scheduling efficiency and speed of the receiving end.
In step S3, the determining the type of the search request further includes: the search request is sent to a type decision device that decides the type of search request, such as, without limitation, alphanumeric characters, voice, still pictures, video, code segments, applications, or the like.
In step S3, the further input into the search processing module further comprises step S31: and (5) comparing. The comparing step of step S31 further includes: step S311, the search processing module compares the search request with the search records of the same type in the search record list stored on the search processing module according to the judged type of the search request, and judges the correlation degree of the search request and the search records; in step S312, if the correlation between the two records exceeds the first threshold, the destination record of the search record whose correlation exceeds the first threshold is retrieved from the search record list stored in the search processing module, and the location in the big data environment linked to the destination record is mapped, and the associated content of the location is retrieved and returned to the search processing module; the search processing module encrypts data according to needs to form a search packet and sends the search packet to a receiving end; in step S313, if the correlation between the two does not exceed the first threshold, the search processing module performs a subsequent search.
Preferably, after the step S3, the method further comprises the step S32: dividing the search request S after determining the search request type into one or more sub-requests SiI is a positive integer, where s is the smallest searchable unit when the search request is the smallest searchable unit (e.g., a single search object that cannot be further split)iIs one, otherwise is a plurality, where S ═ { S ═ S1，……，si，……，sPAnd P is the number of the sub-requests and is a positive integer.
Preferably, after the step S3, the method further comprises the step S33: based on sub-request siAnd the semantic processing module is used for effectively expanding. The step S33 of performing effective expansion by the semantic processing module further includes: step S331: first module of semantic processing module analyzes sub-request siDetermining semantics of the user request, and associating the semantics with the determined concept or object; step S332, the semantic processing module sends a call request to the synonym/near-synonym semantic database, wherein the call request includes a sub-request SiThe information of (a); step S333, after traversing the synonym/near-synonym meaning database, returning a calling result as a calling response; in step S334, the semantic processing module receives the call response and sends the call response to the search processing module. Preferably, the semantic processing module sends the sub-request s to the search processing module through a second module of the semantic processing module after receiving the call response and before sending the call response to the search processing moduleiAnd expanding the words by using a plurality of language expression modes, packaging the words and the call response sent by the synonym/near-synonym meaning database and sending the words and the call response to the search processing module.
Preferably, in step S5, the method further includes: step S51, the search processing module instructs the extraction module to extract the characteristics of the unit source data; step S52, the search processing module traverses the extracted features of the unit source data based on the call response, performs correlation matching between the call response and the extracted features of the unit source data, and records the matching frequency according to different parts of the unit source data; step S53, if the matching condition is satisfied, the matching event is sent to the event processing module; in step S54, the search processing module traverses all the source data and sends each matching event to the event processing module. Such as, but not limited to, a name, abstract, full text, keyword portion, etc.
Preferably, in step S6, the method further includes: in step S61, the event processing module counts the total matching metric, i.e. the degree of correlation, M of the individual source data according to the received event and the recorded matching frequency of different parts of the unit source dataijWherein
Where Q is the total number of different portions of the unit source data, mjDenotes the number of matches in the jth part of the unit source data, and wjRepresents the weight of the jth portion of the unit source data. In step S62, the event processing module performs statistical sorting according to the respective unit data sources. In step S63, the search results are displayed in order from high to low according to the degree of correlation.
In this context, the source data may preferably be, for example, one or more web pages or a collection or combination thereof, as well as any data source known to those skilled in the art.
In a more specific embodiment, if a search request is the smallest searchable unit, i.e., a single sub-request siThe weight of a keyword part is the highest, such as 1.0, according to the frequency of occurrence of different parts in the unit source data and the weight of the different parts; the title portion has a higher weight of 0.85; the weight of the abstract part is higher and is 0.8; the weight of the whole text part is slightly lower and is 0.4; the remaining part has the lowest weight of 0.1. The sorting is carried out according to the matching situation,the search result having the highest statistical value is preferentially displayed at the top as the most relevant search result.
Furthermore, the invention relates to a high-speed information retrieval system for carrying out all or part of the steps of the above method.
By the method and the system, information retrieval can be performed rapidly, accurately and comprehensively, and the safety of the client/retrieval end is ensured.
In summary, in the technical solution of the present invention, by using a high-speed information retrieval method and system, the search speed and efficiency can be improved, the precision ratio and the recall ratio can also be improved, and an inappropriate search request can be excluded in advance to reduce the search time, reduce unnecessary occupation of resources of the receiving end, further increase the workload and energy consumption of the receiving end, and reduce the data scheduling efficiency and speed of the receiving end.
It will be understood that: the examples and embodiments of the invention may be implemented in hardware, software, or a combination of hardware and software. As mentioned above, any body performing such a method may be stored in the form of volatile or non-volatile storage, for example a storage device like a ROM, whether erasable or rewritable or not, or in the form of memory, such as for example a RAM, a memory chip, a device or an integrated circuit or on an optically or magnetically readable medium such as for example a CD, a DVD, a disk or a tape. It will be understood that: storage devices and storage media are examples of machine-readable storage suitable for storing one or more programs that, when executed, implement examples of the present invention. Examples of the present invention may be conveyed electronically via any medium, such as a communication signal carried over a wired or wireless connection, and the examples contain the same where appropriate.
It should be noted that: because the invention solves the technical problems that the searching speed and the searching efficiency can be improved, the precision and the recall ratio can also be improved, and the improper searching request can be eliminated in advance to reduce the searching time, the unnecessary occupation of the resources of the receiving end can be reduced, the workload and the energy consumption of the receiving end can be further increased, and the data scheduling efficiency and the data scheduling speed of the receiving end can be reduced, the technical means which can be understood by technicians in the technical field of computers according to the teaching after reading the specification is adopted, and the technical effects that the searching speed and the searching efficiency can be improved, the precision and the recall ratio can also be improved, the improper searching request can be eliminated in advance to reduce the searching time, the unnecessary occupation of the resources of the receiving end can be reduced, the workload and the energy consumption of the receiving end can be further increased, and the data scheduling efficiency and the data scheduling speed of the receiving end, the measures claimed in the attached claims are therefore subject to the technical solutions in the sense of patent law. Furthermore, the solution claimed in the appended claims has utility since it can be manufactured or used in industry.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A high-speed information retrieval method, comprising:
in step S1, the user inputs and sends a search request from the client;
in step S2, the receiving end performs security authentication on the received search request;
in step S3, if the authentication is passed, the search request is subjected to type determination, and then further input into the search processing module;
in step S4, if not, sending a search response containing rejection information to the client;
in step S5, the search processing module performs a high-speed search; and
in step S6, the search results are displayed in order from high to low according to the degree of correlation;
wherein the step S5 further includes: step S51, the search processing module instructs the extraction module to extract the characteristics of the unit source data; step S52, the search processing module traverses the extracted features of the unit source data based on the call response, performs correlation matching between the call response and the extracted features of the unit source data, and records the matching frequency according to different parts of the unit source data; step S53, if the matching condition is satisfied, the matching event is sent to the event processing module; step S54, the search processing module traverses all source data and sends each matching event to the event processing module;
wherein the step S6 further includes: in step S61, the event processing module counts the total matching metric, i.e. the degree of correlation, M of the individual source data according to the received event and the recorded matching frequency of different parts of the unit source dataijWherein
Where Q is the total number of different portions of the unit source data, mjDenotes the number of matches in the jth part of the unit source data, and wjA weight representing a jth part of the unit source data; step S62, the event processing module carries out statistic ordering according to each unit data source; in step S63, the search results are displayed in order from high to low according to the degree of correlation.
2. The high-speed information retrieval method of claim 1, wherein the receiving end performing security authentication on the received search request in step S2 further comprises: the client that sends the search request to the receiver is authenticated, including the security of the client's search request, the eligibility to authorize access to the receiver, and the legitimacy of the search request content.
3. The high-speed information retrieval method of claim 2, wherein the type-determining the search request in step S3 further comprises: the search request is sent to a type judging device, and the type judging device judges the type of the search request, wherein the type at least comprises character and number characters, voice, static pictures, videos, code segments and application programs.
4. The high-speed information retrieval method of claim 3, wherein in the step S3, the further inputting into the search processing module thereafter further comprises the step S31: a comparison step; the comparing step of step S31 further includes: step S311, the search processing module compares the search request with the search records of the same type in the search record list stored on the search processing module according to the judged type of the search request, and judges the correlation degree of the search request and the search records; in step S312, if the correlation between the two records exceeds the first threshold, the destination record of the search record whose correlation exceeds the first threshold is retrieved from the search record list stored in the search processing module, and the location in the big data environment linked to the destination record is mapped, and the associated content of the location is retrieved and returned to the search processing module; the search processing module encrypts data according to needs to form a search packet and sends the search packet to a receiving end; in step S313, if the correlation between the two does not exceed the first threshold, the search processing module performs a subsequent search.
5. The high-speed information retrieval method of claim 4, wherein after the step S3, further comprising the step S32: dividing the search request S after determining the search request type into one or more sub-requests SiI is a positive integer, where s is the smallest searchable unit when the search request isiIs one, otherwise is a plurality, where S ═ { S ═ S1，……，si，……，sPAnd P is the number of the sub-requests and is a positive integer.
6. The high-speed information retrieval method of claim 5, wherein after the step S3, further comprising the step S33: based on sub-request siThe semantic processing module is used for effectively expanding; the step S33 of performing effective expansion by the semantic processing module further includes: step S331: first module of semantic processing module analyzes sub-request siDetermining semantics of the user request, and associating the semantics with the determined concept or object; step S332, the semantic processing module sends a call request to the synonym/near-synonym semantic database, wherein the call request includes a sub-request SiThe information of (a); step S333, after traversing the synonym/near-synonym meaning database, returning a calling result as a calling response; in step S334, the semantic processing module receives the call response and sends the call response to the search processing module.
7. The high-speed information retrieval method of claim 6, wherein the semantic processing module sends the sub-request s through the second module of the semantic processing module after receiving the call response and before sending to the search processing moduleiAnd expanding the words by using a plurality of language expression modes, packaging the words and the call response sent by the synonym/near-synonym meaning database and sending the words and the call response to the search processing module.
8. A high-speed information retrieval system for executing the high-speed information retrieval method recited in any one of claims 1 to 7.
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| US8799257B1 (en) * | 2012-03-19 | 2014-08-05 | Google Inc. | Searching based on audio and/or visual features of documents |
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| CN1991829A (en) * | 2005-12-29 | 2007-07-04 | 陈亚斌 | Searching method of search engine system |
| CN101404576A (en) * | 2008-09-27 | 2009-04-08 | 深圳市迅雷网络技术有限公司 | Network resource query method and system |
| CN102622453A (en) * | 2012-04-20 | 2012-08-01 | 北京邮电大学 | Body-based food security event semantic retrieval system |
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