CN111190993A

CN111190993A - Hierarchical sorting method based on ordered set of keywords

Info

Publication number: CN111190993A
Application number: CN201911367322.9A
Authority: CN
Inventors: 赵成军
Original assignee: Aerospace Information Co Ltd Enterprise Service Branch
Current assignee: Aerospace Information Co Ltd Enterprise Service Branch
Priority date: 2019-12-26
Filing date: 2019-12-26
Publication date: 2020-05-22

Abstract

The invention provides a hierarchical sorting method based on a keyword ordered set, which comprises the following steps: obtaining an ordered set of keywords, wherein each keyword has an index; combining the keywords in the keyword ordered set to form different subsets; and grading and sequencing the subsets to obtain a keyword ordered combination set. The method is based on the 'keyword sequence set' and the 'keyword ordered combination set', emphasizes ordered sequence and combination classification, supports diversified processing of keywords, words and sentences, accurately matches results on the whole, effectively improves retrieval precision, and has flexibility and usability.

Description

Hierarchical sorting method based on ordered set of keywords

Technical Field

The invention relates to the field of computer technology retrieval, in particular to a related technology and a method for searching an engine, sorting and optimizing a result set, and particularly relates to a hierarchical sorting method based on a keyword ordered set.

Background

The modern society is an era of information explosion, and how to search and extract desired information from mass data is an important technology. Related technologies based on keyword retrieval, sorting and optimization are more, and a common method is simple and mechanical query or combined query according to one or more keywords. A better method is to add a dictionary containing characteristics such as a weight system and the like or introduce an algorithm to calculate the characteristics such as the weight and the like, and sort and select results, so that the matching degree of the query is improved to a certain extent.

The method is based on a 'keyword ordered set' and a 'keyword ordered combination set', emphasizes ordered sequence and combination grading, supports diversified processing of keywords, words and sentences, accurately matches results on the whole, effectively improves retrieval precision, and has certain flexibility and usability.

Disclosure of Invention

In order to solve the problems of the prior art, the invention provides a hierarchical sorting method based on a keyword ordered set, which comprises the following steps:

obtaining an ordered set of keywords, wherein each keyword has an index;

combining the keywords in the keyword ordered set to form different subsets;

and grading and sequencing the subsets to obtain a keyword ordered combination set.

Further, the ranking of the subsets comprises:

a first level, corresponding to a subset comprising 1 keyword;

the second level, corresponding to a subset combined by 2 keywords;

……

and the Nth level corresponds to a subset formed by combining N keywords, wherein N is a natural number.

Further, the index of the subset is formed by combining the indexes of the keywords of the subset from small to large;

the subsets of the same level are sorted according to indexes, and the smaller the index is, the higher the ranking is, the higher the goodness is.

Further, from the first level to the Nth level, the levels are increased step by step, and the higher the level is, the higher the ranking is, the higher the goodness is.

Further, the keywords in the keyword ordered set are divided into a plurality of groups, the keywords in each group are combined to form different subsets, and the plurality of groups of keywords form a plurality of groups of different subsets.

Furthermore, grading and sequencing a plurality of groups of different subsets to obtain a keyword ordered combination set.

Further, obtaining an ordered set of keywords comprises setting an index for the keywords in the order in which the keywords were entered by the user.

Further, aiming at the sentences input by the user, extracting each keyword by using a word segmentation method;

and distributing a weight coefficient to the extracted keywords, and setting indexes for the keywords based on the weight coefficient.

Further, each subset element is used for query retrieval, and a corresponding result set is obtained.

Further, each result in the result set has the same ranking and index as the corresponding subset, and is sorted by rank and index.

The invention provides a hierarchical sorting method based on ordered sets of keywords. The method has the following characteristics and advantages:

first, order and sequence. The method is based on the 'ordered set of keywords' and the 'ordered combined set of keywords', and emphasizes the importance of the keyword sequence and the keyword combined sequence. The dimensions of the weight coefficient, the order of user input, the part of speech and the like can be regarded as the embodiment of the sequential index. The smaller the index, the higher the ordering should be. The earlier subsets indicate a higher goodness of search, i.e., the results obtained by performing information search in this order of sets are relatively good.

And secondly, combination grading. In the method, the keywords are grouped and classified to form each subset. The more the number of the keywords in the subset is, the higher the rank of the subset is, the higher the goodness of search is, that is, the result obtained by performing information retrieval according to the high-rank subset is relatively excellent.

And thirdly, supporting diversification of keywords, words and sentences. And processing, analyzing and extracting phrases or sentences containing the keyword sequences by using a data cleaning or word segmentation technology. The user input is characters, words or sentences, which can be effectively processed, and the flexibility and the usability of the application are improved.

The method is based on the 'keyword sequence set' and the 'keyword ordered combination set', emphasizes ordered sequence and combination classification, supports diversified processing of keywords, words and sentences, accurately matches results on the whole, effectively improves retrieval precision, and has certain flexibility and usability.

Drawings

The above and other objects, features and advantages of the present disclosure will become more apparent by describing in greater detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.

FIG. 1 is a flow chart of the hierarchical ranking method based on ordered sets of keywords of the present invention.

Fig. 2 is a flowchart of a hierarchical sorting method based on ordered sets of keywords according to a first embodiment of the present invention.

FIG. 3 is a flowchart of a hierarchical ranking method based on ordered sets of keywords according to a second embodiment of the present invention.

Fig. 4 is a schematic diagram of subset characteristics in the keyword ordered combination set when there are two keywords according to the fourth embodiment of the present invention.

Fig. 5 is a subset characteristic correspondence table in the keyword ordered combination set in the fourth embodiment of the present invention when there are two keywords.

Fig. 6 is a schematic diagram of subset characteristics in the keyword ordered combination set when there are three keywords according to a fifth embodiment of the present invention.

Fig. 7 is a subset characteristic correspondence table in the keyword ordered combination set when there are three keywords according to the fifth embodiment of the present invention.

FIG. 8 is a flowchart of the sixth embodiment of the present invention for forming an ordered result set from the retrieved information.

FIG. 9 is a flowchart of the optimization and expansion process of retrieving information to form an ordered result set according to the seventh embodiment of the present invention.

Detailed Description

Preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

As shown in FIG. 1, the present invention provides a hierarchical sorting method based on ordered sets of keywords, which comprises:

obtaining an ordered set of keywords, wherein each keyword has an index;

combining the keywords in the keyword ordered set to form different subsets;

Specifically, text is first entered before the ordered set of keywords is obtained. The format of the input text may be a sequence phrase containing keywords/words (hereinafter collectively referred to as "keyword" keys, abbreviated as K) or may be a complete sentence.

Next, an ordered set of keywords is obtained.

1. Phrase against keyword sequences

And (4) carrying out data cleaning, including processes of space removal, meaningless symbol removal, repetition removal and the like.

2. For complete sentences

And extracting each keyword by using a word segmentation method.

3. This step finally forms a keyword set: { Ka, Kb, Kc … }

The keywords in the set are ordered in sequence to obtain a "keyword ordered set", that is, an ordered set of keywords:

{ K1, K2 … Kn }, where n is the index;

the "ordering", i.e., ordering, indexing. The key words are sorted in sequence, specifically:

1. for the keyword sequence:

the order of the user input sequence is used as the sequential index, because the user input order represents the importance of the content to be searched, and represents the weight coefficient. The more advanced keywords are, the higher the importance degree is and the larger the weight coefficient is.

2. For the sentence:

the order of priority ordering of the keyword characteristic values obtained by the word segmentation method according to the dimensions such as weight, part of speech and the like is used as a sequence index.

The smaller the sequence index is, the higher the ranking is, and the higher the corresponding goodness is. The "goodness of search" refers to the degree of goodness of the result obtained by performing information retrieval according to a certain keyword or a set thereof. The higher the goodness, the better the result of the query.

Theoretically, the keyword or set with larger weight coefficient has higher goodness of inspection; the greater the number of keywords matched and hit by the query, the higher the goodness of the query.

For example: an ordered set of keywords formed from three keywords: { K1, K2, K3}, which contains three keywords in total, K1, K2 and K3, and the goodness K1> K2> K3 is sequential. Further, the result set corresponding to the two keywords K1 and K2 is better than the result set corresponding to only one keyword K1.

Next, the keywords are combined to form the subset Kc.

Combining different keys Ki … Kj in the ordered set of keys { K1, K2 … Kn } may form different subsets (abbreviated Kc, denoted Ki … j, where i, j are the sequential indices of keys). Subsequent processes query, retrieve, and use each subset to correspond to a corresponding query result set (denoted as Si … j, where i, j is the sequential index of Key).

For example: in the case of two keys, the ordered set of keywords is: { K1, K2}, which can be combined with one another to form subsets: { K1, K2, K12}, corresponding to the query result set: { S1, S2, S12 }. Where K12 represents a subset of key combinations formed by two keys K1 and K2. The corresponding S12 represents the result set obtained by querying and retrieving according to K12.

Finally, a "key ordered set of combinations" is formed. Through the steps, all the formed subsets Kc are sorted in order and in a grading way, and a 'keyword ordered combination set' is obtained. Similarly, the subsequent query and search using each subset element also corresponds to a corresponding result set, and the difference is that the corresponding result set is ordered as a whole, and the smaller the index, the higher the rank, and the better the result.

For example, the sequential ordering process of the subsets follows the following principle:

1. ordering (Sequential, Seq for short):

when the subsets are ordered in sequence, the subsets are kept consistent with the order of indexes in the ordered set of the keywords as much as possible, and the smaller the index is, the higher the index is, the more the subset is arranged in the front. The more advanced subsets indicate higher goodness, i.e., the results obtained by performing information retrieval in this set order are superior.

2. Hierarchical (levelled, abbreviated Lev):

lev1, corresponding to a combined subset of 1 keyword; lev2, corresponding to a combined subset of two keywords; the LevN corresponds to a subset of N key combinations. The more the number of the keywords in the subset is, the higher the rank of the subset is, the higher the goodness of search is, that is, the result obtained by performing information retrieval according to the high-rank subset is relatively excellent.

The principle of ordering and grading in the sorting process of the subsets determines:

the more consistent the index order for keys in a subset of the same level Lev (i.e., having the same number of keys) is with the "key sorting table" order index, the higher the goodness. For example: same Lev goodness: k12> K13, ranking K12 before K13;

the Lev sets in different levels are ranked more forward the higher the level is, so that a relatively high degree of goodness of search can be obtained. Namely: goodness at different Lev: subset in LevN > subset in LevN-1, rank: the subset in LevN is more advanced than the subset of LevN-1.

The method is based on the 'ordered set of keywords' and the 'ordered combined set of keywords', and emphasizes the importance of the keyword sequence and the keyword combined sequence. Each keyword in the keyword ordered set has an index, and various dimensions such as the size of a weight coefficient, the order of user input, the part of speech and the like can be regarded as embodying of the order index. The smaller the index, the higher the ordering should be. The earlier subsets indicate a higher goodness of search, i.e., the results obtained by performing information search in this order of sets are relatively good.

In the method, the keywords are grouped and classified to form each subset. The more the number of the keywords in the subset is, the higher the rank of the subset is, the higher the goodness of search is, that is, the result obtained by performing information retrieval according to the high-rank subset is relatively excellent.

Further, the keywords in the keyword ordered set are divided into a plurality of groups, the keywords in each group are combined to form different subsets, and the plurality of groups of keywords form a plurality of groups of different subsets. And grading and sequencing the plurality of groups of different subsets to obtain a keyword ordered combination set.

Further, aiming at the sentences input by the user, extracting each keyword by using a word segmentation method; and distributing a weight coefficient to the extracted keywords, and setting indexes for the keywords based on the weight coefficient.

The invention supports diversification of keywords, words and sentences. And processing, analyzing and extracting phrases or sentences containing the keyword sequences by using a data cleaning or word segmentation technology. The user input is characters, words or sentences, which can be effectively processed, and the flexibility and the usability of the application are improved.

To facilitate understanding of the solution of the embodiment of the present invention and the effect thereof, a specific application example of the method of the present invention is given below. It will be understood by those skilled in the art that this example is merely for the purpose of facilitating an understanding of the present invention and that any specific details thereof are not intended to limit the invention in any way.

The invention comprises the following steps, which are combined with the necessary figures, tables and flows in order to explain the implementation of each step in detail. Simple steps are simply illustrated, and important and complex steps are added with more detailed steps for further explanation.

The first embodiment is as follows:

FIG. 2 is a flowchart of a hierarchical ranking method based on ordered sets of keywords according to an embodiment of the present invention. As shown in FIG. 2, the detailed steps for forming the "key ordered combination set" from the "key ordered set" are as follows:

1. the number N of keys in the key ordered set { K1, K2 … Kn } is computed. If N is 0, directly ending, otherwise, continuing the following steps;

2. initializing M ═ N and an empty set S { };

3. sequentially calculating sets corresponding to LevM of each level from a high level to a low level, and adding all the obtained subsets Kc to the tail end of the set S;

4. and (5) making M equal to M-1, if M is not 0, repeating the step 3, otherwise, ending the step, and obtaining the key ordered combination set by S.

Example two:

FIG. 3 is a flowchart of a hierarchical ranking method based on ordered sets of keywords according to a second embodiment of the present invention. As shown in fig. 3, a subset in LevM is a subset formed by combining M keys. The detailed steps of the calculation method are as follows:

2. initializing i ═ 1, j ═ m, and an empty set S { };

3. taking out continuous keywords Ki, Ki +1 … Kj from the set according to the index number, and taking out M keywords to form one Kc of the subsets of the level;

4. appending the subset Kc to the end of the set S;

5. a new round of Kc extraction process: let j equal j + 1;

6. if j < ═ N, the first M-1 keys of the previous round of Kc are also taken out and the sequence is not changed, and then a new Kj +1 is taken out to be used as a new subset Kc. Repeating the step 4;

otherwise, let i equal to i +1, if i + M-1> -N, the procedure is ended, and the set S is the subset result in LevM. Otherwise, repeat step 3.

Example three:

this embodiment gives the case of only one Key (K1):

only one key K1 is in its simplest form. K1 can only form a set of keys that contains one key, and there is only one level, Lev 1. The key word of K1, the corresponding query result set is S1, which is also the total result set S.

Example four:

fig. 4 is a schematic diagram of subset characteristics in the keyword ordered combination set when there are two keywords according to the fourth embodiment of the present invention. As shown in fig. 4, the case of two keys (K1, K2):

ordered set of keywords: { K1, K2}

And (3) ordered combination set of keywords: { K12, K1, K2}, goodness: k12> K1> K2

Grade: lev2, Lev1, goodness: lev2> Lev1

The subset of ordered query results { S12, S1, S2}, count (S) -3.

Under the condition of two keys, a subset characteristic corresponding relation table in the ordered combination set of the Key words refers to fig. 5.

Example five:

fig. 6 is a schematic diagram of subset characteristics in the keyword ordered combination set when there are three keywords according to a fifth embodiment of the present invention. As shown in fig. 6, the case of three keys:

ordered set of keywords: { K1, K2, K3}

And (3) ordered combination set of keywords: { K123, K12, K13, K23, K1, K2, K3}

Grade: lev3, Lev2, Lev 1. And (4) checking the goodness: lev3 Lev2 Lev1

Query result set S: { S123, S12, S13, S23, S1, S2, S3}

count(S)＝7。

In the case of three keys, the subset characteristics in the ordered set of keys refer to fig. 7.

Next, a process of retrieving information by using the ordered combination set of keywords formed by the method of the present invention to form an ordered result set will be described.

1. Traversing the ordered key word combination set, and sequentially extracting subsets according to the index sequence;

2. sequentially using the extracted subsets to retrieve information and obtaining corresponding result sets;

3. and performing additional fusion on the result sets of the subset retrieval to form a final result set S. The results thus formed are also sequential. The smaller the order index, the better the result.

Example six:

FIG. 8 is a flowchart of the sixth embodiment of the present invention for forming an ordered result set from the retrieved information. As shown in fig. 8, 1, initialize an empty result set S;

2. traversing the ordered combination set of the keywords, and sequentially extracting the subsets according to the index order;

3. retrieving information by using the extracted subset, and obtaining a corresponding result set Sc;

4. adding the result set Sc to the end of the result set S;

5. whether all subsets have been traversed, if not, returning to the step 2; otherwise, ending.

Through the above steps, a preferred result set is derived, which can be output or pushed.

Furthermore, in the step of 'retrieving information and forming an ordered result set', the limit of the result number MaxCount (S) can be introduced, and when the MaxCount is reached, the retrieval process can be directly ended and the query result can be returned, so that the retrieval efficiency and the resource consumption of the whole process can be optimized.

Example seven:

FIG. 9 is a flowchart of the optimization and expansion process of retrieving information to form an ordered result set according to the seventh embodiment of the present invention. As shown in fig. 9:

1. firstly, appointing Max _ Count limit, initializing an empty result set S, and initializing to obtain a result number Num as Max _ Count;

3. retrieving information by using the extracted subsets, and obtaining a corresponding result set Sc and a result quantity Ci;

4. comparing whether Num is larger than Ci, if so, adding the result set Sc to the end of the result set S, and updating Num-Num-Ci; if not, extracting the first Num results from the result set Sc, and adding the results to the end of the result set S;

Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A hierarchical ordering method based on ordered sets of keywords is characterized by comprising the following steps:

obtaining an ordered set of keywords, wherein each keyword has an index;

combining the keywords in the keyword ordered set to form different subsets;

2. The method of claim 1, wherein the ranking of the subsets comprises:

3. The method of claim 2, wherein the indexes of the subsets are combined from small to large by combining the indexes of the keywords of the subsets;

4. The method according to claim 2, wherein the ranking increases from the first rank to the nth rank, and the higher the ranking, the higher the ranking, and the higher the goodness of the ranking.

5. The method of claim 1, wherein the keywords in the ordered set of keywords are divided into a plurality of groups, the keywords in each group are combined to form different subsets, and the plurality of groups of keywords form a plurality of groups of different subsets.

6. The hierarchical ordering method based on the ordered set of keywords according to claim 5, wherein a plurality of groups of different subsets are graded and ordered to obtain an ordered combination set of keywords.

7. The method of claim 1, wherein obtaining an ordered set of keywords comprises setting an index for the keywords in an order in which the keywords were entered by the user.

8. The hierarchical ranking method based on keyword ordered sets according to claim 1, characterized in that, for the sentence inputted by the user, each keyword is extracted by using a word segmentation method;

9. The method of claim 1, wherein each subset element is used for query search to obtain a corresponding result set.

10. The method of claim 9, wherein each result in the result set has the same rank and index as the corresponding subset and is sorted by rank and index.