CN114519128A - Method for combining and displaying multiple information sources in search automatic completion - Google Patents

Abstract

The invention provides a method for combining and displaying multiple information sources in search automatic completion, which is characterized by comprising the following steps: receiving a search request of a user; searching a prefix tree according to the search terms in the user search request to obtain a candidate completion term result; comparing the similarity between the search word in the user search request and the record name in the affinity relation table, and adding the record name into the candidate completing word result when the similarity reaches a preset threshold value; and sorting and returning the candidate completing word results. The method for combining and displaying multiple information sources in the automatic completion of search enables multiple information sources to be displayed in the candidate frame at the same time. The search requirements of various information in the small red book APP are met, a more convenient search entry is provided for the user, and the use experience of the user is improved.

Description

Method for combining and displaying multiple information sources in search automatic completion

Technical Field

The invention relates to the field of information search, in particular to a method for automatically completing search terms input by a user.

Background

With the advent of the information age, information and data have been growing explosively. The importance of information search is increasingly prominent, and the requirements on the efficiency and accuracy of retrieval are also increasingly high. The automatic completion of the search terms is an important technology for improving the search efficiency and accuracy. The traditional search term automatic completion only focuses on the information of the search term, and the characteristics of an information source and an information base to be retrieved are not considered during completion, so that the completion technology is suitable for general searches of Google, Baidu and the like. But for a particular kind of information source, for example: aiming at one or more specific information sources such as notes, commodities, stars, enterprise numbers and concerned large V, when a user searches, if the user only completes the search words based on the self semantics or completes the search words based on a completion system trained by the data of the whole network search words, the accuracy of the search results is greatly reduced.

In addition, in information sources related to personal information, such as large V and star, the keyword of the retrieval target often contains an unusual character, for example, the real user name of "shandona" is "shandona", and even personalized special characters and character patterns are also provided, and in these cases, it is difficult to complement a proper associative word by using the existing search word automatic complementing mode.

Finally, the existing search completion system generally cannot solve personalized search completion, for example, a user a wants to retrieve a homepage of a user B, but the user B is not a popular or popular user, and the existing search term completion method generally cannot complete automatic completion at this time.

Disclosure of Invention

In view of the above drawbacks of the prior art, an object of the present invention is to provide a method for combining and displaying multiple information sources in search automatic completion, which is used for improving the accuracy of automatic completion of search terms and improving user experience in a specific information source search scenario.

To achieve the above and other related objects, the present invention provides a method for combining and presenting multiple information sources in search autocompletion, comprising: receiving a search request of a user; searching a prefix tree according to the search terms in the user search request to obtain a candidate completion term result; comparing the similarity between the search word in the user search request and the record name in the affinity relation table, and adding the record name into the candidate completing word result when the similarity reaches a preset threshold value; and sorting and returning the candidate completing word results.

Preferably, in the method for combining and presenting multiple information sources in search autocompletion, the prefix tree is constructed by: recording the searching behavior of the user within a period of time T; acquiring the name and ID value of each record in an information source; and constructing the prefix tree according to the user searching behavior and the name and the ID value recorded in the information source.

Preferably, in the method for combining and presenting multiple information sources in search autocompletion, the nodes of the prefix tree include a search term character string, and further include one or more attributes of a record name, an ID value, a heat degree, a category, and a frequency associated with the search term.

Preferably, in the method of integrating and presenting multiple information sources in search autocompletion, the affinity table includes record names and record IDs that are frequently focused by the user.

Preferably, in the method of integrating and presenting multiple information sources in search autocompletion as described above, the logical structure of the affinity table is in the form of a "key-value" pair, where "key" is the ID of the user and "value" is a list of records that the user often focuses on.

Preferably, in the method of combining and presenting multiple information sources in search autocompletion as described above, the record list includes the record name and the record ID.

The invention also provides a prefix tree for automatically completing the search terms, which is characterized by being constructed by the following method: recording the searching behavior of the user within a period of time T; acquiring the name and ID value of each record in an information source; and constructing the prefix tree according to the user searching behavior and the name and the ID value recorded in the information source.

Preferably, in the prefix tree for automatic completion of search terms, nodes of the prefix tree include search term character strings, and further include one or more attributes of record names, ID values, heat degrees, categories, and frequencies related to the search terms.

The method for combining and displaying multiple information sources in search automatic completion enables multiple information sources to be displayed in the candidate frame at the same time. The search requirements of various information in the small red book APP are met, a more convenient search entry is provided for the user, and the use experience of the user is improved.

Drawings

FIG. 1 is a flow chart of the operation of the automatic completion system for search terms according to the present invention.

Detailed Description

The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention.

Please refer to the attached drawings. It should be noted that the drawings provided in the present embodiment are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.

The invention firstly discloses a prefix tree construction method for searching automatic completion. In the existing prefix tree for searching automatic completion, each node is usually composed of a character string of a search term or a substring thereof, and based on the prefix tree, the automatic completion which can be provided can only be based on the semantics of the search term. In order to provide better search automatic completion for user experience based on different information source characteristics, user retrieval habits and the like, a new prefix tree needs to be respectively constructed for each information source, wherein the information sources can be user (enterprise) information sources, commodity information sources, note information sources and the like. The prefix tree construction process of the present invention is as follows.

Firstly, recording the searching behavior of the user within a period of time T, wherein the recorded information can comprise search terms provided by the user, the use frequency of the search terms, the input time of the search terms, the use sequence of the search terms and the like, and specifically recording which information and the number of the T period, and the increase and the deletion can be carried out according to the actual requirement. In this example, assuming that the T period is set to 2 months, the recorded information is described only with a search word for the sake of simplicity of description.

Then, the name and ID value of each record in the information source are obtained. Where the name of the record refers to the field information in the record that facilitates a person's call. Taking a star information source as an example, the information source records information such as a user name, a homepage address, and the like of the star, and the name recorded in the information source is the user name of the star, such as "shanyang na Nana" in the foregoing. The ID value of a record refers to a value that is easy for a computer to identify and is used to uniquely locate the record, and is typically an identifier that the database assigns to each record and that the user uniquely identifies one record. In this step, in addition to the recorded name and ID value, the recorded heat information and category information may be acquired simultaneously as needed.

And finally, constructing a candidate word prefix tree, wherein each node of the prefix tree not only comprises a search word character string, but also comprises information such as record names, ID values, heat degrees, categories, frequencies and the like related to the search words.

It should be noted that, for a user who uses the retrieval system for the first time, since there is no history data of the search behavior, a default prefix tree may be provided for the user, and after there is data of the search behavior of the user, the default prefix tree is modified and adjusted.

In order to better provide personalized autocompletion for the user, it is preferable to construct an affinity list in addition to the prefix tree described above. Through the historical search behaviors of the user, a group of search objects which are frequently concerned by the user can be mined, and an affinity list can be maintained for the user on the basis of the search objects. The logical structure of the list may be in the form of a "key-value" pair, where a "key" may use the user's ID and a "value" may be a list including record names and record IDs that the user often retrieves, focuses on, such as the user name of the star and the record ID of the star. In practice, it is usually necessary to continuously maintain and update the affinity list according to the search behavior record of the user, and the maintenance and update period depends on the application requirement, in this example, the maintenance is performed by once a day.

Based on the prefix tree and the affinity relationship table, the search term completion method of the present invention is shown in fig. 1. The process begins by receiving a search request submitted by a user, including a search term entered by the user.

S1 shows that the search term input by the user searches the prefix tree to obtain the preliminary search completion term result, and the nodes of the prefix tree already contain the information such as the record name, ID value, heat, category, etc., so the candidate completion term result also contains the information.

S2 represents sorting the candidate results. This step is the preferred step and the ranking criteria can be adjusted according to the business and actual needs. In this example, the ranking criteria is the popularity of the search terms, and in some other applications, the ranking may also be based on user preferences, relevance, and other factors.

S3 shows that the high density relation table is checked and the similarity between the search word inputted by the user and the record name in the "value" list of the affinity relation table is compared. If a certain similarity threshold is reached, the record is also added to the candidate list. Taking the star data source as an example, the similarity between the search word input by the user and the star user name in the list is compared, and if the similarity exceeds a preset threshold value, the record of the star is also added into the candidate list. In this step, further optimization can be performed for the characteristics of the information source: for example, for the note information source or the merchandise information source, the number of notes or the number of merchandise may be further shown in the candidate list.

The above only describes the processing steps for one information source, and if there are multiple information sources, the above steps may be respectively adopted for each information source, and finally, the return results of each information source are integrated and summarized as required and then returned.

In summary, the present invention provides a novel prefix tree, where nodes of the prefix tree can be constructed according to different information source characteristics, and the nodes include the information source characteristics, and based on the novel prefix tree, the search terms can be completed based on the semantics of the search terms input by the user, and also can be completed according to the information source characteristics. Preferably, the invention further provides an affinity relationship list, and the affinity relationship list is combined with the novel prefix tree and the affinity relationship list, so that more accurate and personalized search term completion can be provided for the user, and the user experience is improved.

The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Modifications and variations can be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the present invention, for example: when the returned result is displayed to the user, different types of information sources can be distinguished and identified; the above numbering of the steps and the words such as "first" and "second" before the steps are also only for convenience of description, and are not used to limit the order of the steps, and those skilled in the art can perform the steps in parallel, serially, synchronously, asynchronously, or in sequence according to actual situations. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.

Claims (8)

1. A method for combining and presenting multiple information sources in search autocompletion, comprising:

receiving a search request of a user;

searching a prefix tree according to the search terms in the user search request to obtain a candidate completion term result;

comparing the similarity between the search word in the user search request and the record name in the affinity relation table, and adding the record name into the candidate completing word result when the similarity reaches a preset threshold value;

and sorting and returning the candidate completing word results.

2. The method of integrating and presenting multiple information sources in search autocompletion as recited in claim 1, wherein the prefix tree is constructed by:

recording the searching behavior of the user within a period of time T;

acquiring the name and ID value of each record in an information source;

and constructing the prefix tree according to the user searching behavior and the name and the ID value recorded in the information source.

3. The method of claim 2, wherein the nodes of the prefix tree comprise a search term string and further comprise one or more attributes of record name, ID value, heat, category, frequency associated with the search term.

4. The method of integrating and presenting multiple information sources in search autocompletion as recited in claim 1, wherein the affinity table comprises record names and record IDs that are of frequent interest to the user.

5. The method for integrating and presenting multiple information sources in search autocompletion according to claim 4, wherein the logical structure of the affinity table is in the form of a "key-value" pair, wherein "key" is the ID of the user and "value" is a list of records that the user is interested in frequently.

6. The method of integrating and presenting multiple information sources in search autocompletion as recited in claim 5, wherein the list of records comprises the record name and the record ID.

7. A prefix tree for automatic completion of search terms is characterized by being constructed by the following method:

recording the searching behavior of the user within a period of time T;

acquiring the name and ID value of each record in an information source;

and constructing the prefix tree according to the user searching behavior and the name and the ID value recorded in the information source.

8. The method of claim 7, wherein the nodes of the prefix tree comprise a search term string and further comprise one or more attributes of record name, ID value, heat, category, frequency associated with the search term.

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