JP2019128622A - Device for evaluation of retrieval word, evaluation system and evaluation method - Google Patents

Abstract

To provide an evaluation device, an evaluation system, and an evaluation method for quantitatively evaluating how an upper page of a search result of a search term to be subjected to SEO in accordance with changes with time.SOLUTION: An evaluation method includes: an input step SA100 in which a search term is input; an acquisition step SA110 in which search result data of search based on the search term at a first time point is acquired, and search result data of search based on the search term at a second time point different from the first time point is acquired; and an analysis step SA120 in which an index indicating a correlation between search result data at the first time point and search result data at the second time point is obtained and the index is output as an analysis result unique to the search term.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a technique for evaluating a change tendency of a search result for each search word in a search system.

  Various technologies have been proposed to support SEO (Search Engine Optimization). There is Patent Document 1 as a document disclosing this kind of technology. The web page analysis apparatus disclosed in Patent Document 1 uses a plurality of web page data in a search result for a target keyword as an analysis target web page when a certain search term is input as a target keyword, and the analysis target web page data Perform morphological analysis processing, count the number of contents of each morpheme of the same type in the morpheme group obtained by the morphological analysis processing, and indicate the degree of contribution of each morpheme to the order of the analysis target web page in the search result An evaluation value is obtained, and a list in which evaluation values classified by morpheme are arranged for each analysis target web page is presented as an analysis result. According to the technique of Patent Document 1, a morpheme having a high SEO effect can be found efficiently.

Japanese Patent No. 6164436

  By the way, some of the search terms used as search queries for search engines are those in which the headlines of the upper page of the search results change rapidly in a short period of time, the headlines of the upper page of the search results substantially change over a long period of time Some do not. The size of the personal and budgetary resources required to keep the priority of the countermeasure target page or content in the search results of a certain search term largely depends on how rapidly the top of the search results of the search term changes. Do. For this reason, companies that conduct SEO and marketing, especially retailers who handle hundreds, thousands, or more than thousands of articles, mail-orders, manufacturers, portal sites, etc., search terms related to their articles. There is a strong need to quantitatively evaluate how much it is necessary to respond in line with changes in current trends, and to use it as an indicator of the resource allocation of the company.

  However, the technique of Patent Document 1 performs analysis by analyzing only a plurality of web page data in the search result at the time of analysis, and is not suitable for evaluating the temporal change of the upper page of the search result for each search word. Met.

  The present invention has been made in view of such problems, and is a technology for quantitatively evaluating how top pages of search results related to SEO and marketing change as time passes. The purpose is to provide an effective means.

  In order to solve the above-mentioned subject, the evaluation device of the search word which is a suitable mode of the present invention acquires the search result data of the search based on the search word based on the input means where the search word is input and the first time point Acquisition means for acquiring search result data of the search based on the search term at a second time point different from the first time point, search result data of the first time point, and a search of the second time point An analysis means for obtaining an index indicating a correlation with the result data and outputting the index as an analysis result unique to the search term is provided.

  In this aspect, there may be designated means for designating at least one of the first time point and the second time point.

  In addition, the search result data is N (N is a natural number of 2 or more natural number) documents ranked high in the search result when the search based on the search term is performed from the document data group described in the markup language. The analysis means is an order of data, and operates the order of the N document data at the first time point and the order of the N document data at the second time point on a predetermined function, You may make it obtain | require the parameter | index which shows the said correlation.

Further, the second time point is a time point before the first time point, and the analysis means determines a time difference between the first time point t and the second time point as d, at the first time point t. An index based on the order or rank of the i-th document data out of N document data is x (t) _i , the average value of the index is xm (t), the N at the second time point t-d Assuming that an index based on the order or rank of the i-th document data among x pieces of document data is x (t−d) _i and an average value of the indices is xm (t−d), the following equation An index ((t, d) indicating the correlation may be obtained according to the function shown in (1).

  In addition, the search result data is N (N is a natural number of 2 or more natural number) documents ranked high in the search result when the search based on the search term is performed from the document data group described in the markup language. Snippet analysis data obtained by performing predetermined analysis processing on a snippet of data, wherein the analysis means is the N snippet analysis data at the first time point and the N snippet analysis at the second time point You may obtain | require the parameter | index which shows the said correlation by making data act on a predetermined function. .

Further, the second time point is a time point before the first time point, and the analysis means determines a time difference between the first time point t and the second time point as d, at the first time point t. The index based on the snippet analysis data or the snippet analysis data of the i-th document data in the N document data is x (t) _i , the average value of the index is xm (t), and the second time point t− The index based on the snippet analysis data or the snippet analysis data of the i-th document data in the N document data in d is x (td) _i , and the average value of the index is xm (td) In this case, an index ρ (t, d) indicating the correlation may be obtained according to a function shown in the following formula (1).

  The search word evaluation system according to another preferred embodiment of the present invention includes a user terminal and an evaluation device communicating with the user terminal, the evaluation device including an input unit to which a search word is input Acquisition means for acquiring search result data of a search based on the search term at a first time, and acquiring search result data of a search based on the search term at a second time different from the first time Analyzing means for obtaining an index indicating a correlation between the search result data at the first time point and the search result data at the second time point, and outputting the index as an analysis result specific to the search word. It features.

  According to another preferred aspect of the present invention, there is provided a method of evaluating a search term, which comprises: an input step of inputting a search term; acquiring search result data of a search based on the search term at a first time; Acquisition step of acquiring search result data of the search based on the search term at a second time point different from the time point, correlation of the search result data of the first time point and the search result data of the second time point An analysis step of obtaining an index to be displayed and outputting the index as an analysis result unique to the search term.

  According to another preferred aspect of the present invention, a search term evaluation apparatus comprises: input means for inputting a search term; and access analysis data of an access destination in search results of a search based on the search term at a first time point Acquisition means for acquiring the access analysis data of the access destination in the search result of the search based on the search term at the second time point different from the first time point, and the access analysis data at the first time point And an analysis means for obtaining an index indicating the correlation between the access analysis data at the second point in time and the access analysis data at the second time point, and outputting the index as an analysis result unique to the search word.

  In this aspect, there may be designated means for designating at least one of the first time point and the second time point.

  The access analysis data includes N (N is the highest click-through rate at the address of the document data in the search result when a search based on the search word is performed from the document data group described in the markup language. 2) a click-through rate of the document data, and the analyzing unit is configured to select the click-through rate of the N document data at the first time point and the N document data at the second time point. The index indicating the correlation may be obtained by applying the click-through rate to a predetermined function. .

In addition, the second time point is a time point before the first time point, and the analysis unit sets the time difference between the first time point t and the second time point to d, and the time point at the first time point t. The click-through rate of N document data is the click-through rate of the i-th document data or the index based on the click-through rate of the document data x (t) _i , the average value of the index is xm (t), the second time point The click through rate of the N pieces of document data at t−d is the click through rate of the i th document data or the index based on the click through rate of the document data x (t−d) _i , and the average value of the index If t−d), the index ρ (t, d) indicating the correlation may be obtained according to the function shown in the following formula (1).

  In the access analysis data, N (N is 2) where the residence time in the address of the document data in the search result is high when the search based on the search word is performed from the document data group described in the markup language. Stay time of the document data of the above natural numbers), and the analysis means determines the stay time of the N document data at the first time and the stay time of the N document data at the second time By acting on a predetermined function, an index indicating the correlation may be obtained. .

In addition, the second time point is a time point before the first time point, and the analysis unit sets the time difference between the first time point t and the second time point to d, and the time point at the first time point t. An index based on the stay time or the stay time of the i-th document data among the N document data is x (t) _i , the average value of the index is xm (t), and the second time point t−d. An index based on the stay time or the stay time of the i-th document data among the N document data in X is x (t−d) _i , and the average value of the index is xm (t−d). In this case, an index ρ (t, d) indicating the correlation may be obtained according to the function shown in the following formula (1).

  Further, the access analysis data includes N (N is 2), which has a higher leaving rate at the address of the document data in the search result when searching based on the search word from the document data group described in the markup language. And the analysis means determines the leaving rate of the N document data at the first time and the leaving rate of the N document data at the second time. By acting on a predetermined function, an index indicating the correlation may be obtained. .

Further, the second time point is a time point before the first time point, and the analysis means determines a time difference between the first time point t and the second time point as d, at the first time point t. The index based on the exit rate or exit rate of the i-th document data out of N document data is x (t) _i , the average value of the index is xm (t), and the second time point t−d An index based on the detachment rate or detachment rate of the i-th document data among the N document data in the above is x (t−d) _i , and the average value of the index is xm (t−d). In this case, an index ρ (t, d) indicating the correlation may be obtained according to the function shown in the following formula (1).

  Further, the access analysis data is N (N is 2) in which the number of inflows at the address of the document data in the search result is high when the search based on the search word is performed from the document data group described in the markup language. The above-mentioned analysis means is the inflow number of the N document data at the first time point and the inflow number of the N document data at the second time point. By acting on a predetermined function, an index indicating the correlation may be obtained. .

In addition, the second time point is a time point before the first time point, and the analysis unit sets the time difference between the first time point t and the second time point to d, and the time point at the first time point t. The index based on the number of inflows or the number of inflows of the i-th document data out of N document data is x (t) _i , the average value of the indicators is xm (t), and the second time point td An index based on the number of inflows or the number of inflows of the i-th document data among the N document data in the above is x (t−d) _i , and an average value of the index is xm (t−d). In this case, an index ((t, d) indicating the correlation may be obtained according to a function shown in the following equation (1).

  In the access analysis data, N (where N is 2 or more), the number of browsing pages of the document data in the search result in the search result when the search based on the search word is performed from the document data group described in the markup language. A natural number of browsed pages of the document data, and the analysis means is a browsed page number of the N document data at the first time and a browse page of the N document data at the second time You may obtain | require the parameter | index which shows the said correlation by making a number act on a predetermined function. .

Further, the second time point is a time point before the first time point, and the analysis means determines a time difference between the first time point t and the second time point as d, at the first time point t. The index based on the number of browsing pages or the number of browsing pages of the i-th document data among the N document data is x (t) _i , the average value of the index is xm (t), and the second time point The index based on the number of browsed pages or the number of browsed pages of the i-th document data among the N document data at t-d is x (td) _i , and the average value of the index is xm ( If t−d), the index ρ (t, d) indicating the correlation may be obtained according to the function shown in the following formula (1).

  The search word evaluation system according to another preferred embodiment of the present invention includes a user terminal and an evaluation device communicating with the user terminal, the evaluation device including an input unit to which a search word is input And obtaining access analysis data of an access destination in search results of the search based on the search term at the first time, and search results of the search based on the search term at a second time different from the first time. Obtaining the access analysis data of the access destination of the access point, and obtaining an index indicating a correlation between the access analysis data at the first time point and the access analysis data at the second time point, and using this index as the search term And an analysis means for outputting as a unique analysis result.

  According to another preferred aspect of the present invention, there is provided a method of evaluating a search term, an input step in which a search term is input, and access analysis data of an access destination in search results of a search based on the search term at a first time point. Acquiring the access analysis data of the access destination in the search result of the search based on the search term at the second time point different from the first time point, and obtaining the access analysis data of the first time point And an analysis step of obtaining an index indicating a correlation between the access analysis data at the second point of time and the access analysis data at the second time point, and outputting the index as an analysis result unique to the search word.

  According to the present invention, it is possible to quantitatively evaluate how the upper rank of the search result of the search word changes with time. Therefore, according to the present invention, companies performing SEO and marketing are more likely to allocate resources by distinguishing between the commercial material field that is more likely to respond in line with changes in the current trend and the commercial material field that is not. Can.

It is a figure which shows the whole structure of the evaluation system 1 containing the evaluation apparatus 20 which is 1st Embodiment of this invention. 4 is a flowchart showing a flow of an evaluation method executed by a CPU 22 of the evaluation device 20 according to an evaluation program 26. It is a figure for demonstrating the input processing of the evaluation apparatus. It is a figure for demonstrating the acquisition process and analysis process of the evaluation apparatus. It is a figure for demonstrating the quantitative evaluation of the order | rank using the parameter rho calculated by the analysis process of the evaluation apparatus 20, and the feature analysis of the market based on this quantitative evaluation. It is a figure which shows the whole structure of 1 A of evaluation systems containing 20 A of evaluation apparatuses which are 2nd Embodiment of this invention. It is a figure which shows the whole structure of the evaluation system 1B containing the evaluation apparatus 20B which is 3rd Embodiment of this invention. It is a figure which shows the whole structure of 1 C of evaluation systems containing the evaluation apparatus 20C which is 4th Embodiment of this invention. It is a figure for demonstrating the acquisition process and analysis process of 20 C of evaluation apparatuses. It is a figure which shows the whole structure of evaluation system 1D containing evaluation apparatus 20D which is 5th Embodiment of this invention. It is a figure which shows the whole structure of the evaluation system 1E containing the evaluation apparatus 20E which is 6th Embodiment of this invention. It is a figure for demonstrating the acquisition process and analysis process of the evaluation apparatus. It is a figure for demonstrating the acquisition process and analysis process of 20 C of evaluation apparatuses. It is a figure for demonstrating the acquisition process and analysis process of 20 C of evaluation apparatuses. It is a figure for demonstrating the acquisition process and analysis process of 20 C of evaluation apparatuses. It is a figure for demonstrating the acquisition process and analysis process of 20 C of evaluation apparatuses. It is a figure for demonstrating the quantitative evaluation of the order | rank using the parameter rho calculated by the analysis process of the evaluation apparatus 20, and the feature analysis of the market based on this quantitative evaluation.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
First Embodiment
FIG. 1 is a diagram showing an overall configuration of an evaluation system 1 including an evaluation apparatus 20 according to the first embodiment of the present invention. The evaluation system 1 shown in FIG. 1 is a group of document data (data described in a markup language such as HTML (Hyper Text Markup Language)) scattered as a web site, a web page, or web content on the Internet 90. Thus, when a search based on a certain search word is performed, it is quantitatively evaluated how the upper rank of the search result changes with time.

  As shown in FIG. 1, the evaluation system 1 includes a user terminal 10 and an evaluation device 20. The user terminal 10 and the evaluation device 20 are connected via the Internet 90. A search engine server device 50 is connected to the Internet 90.

  The search engine server device 50 is a device that plays a role of providing a search engine service. The search engine server device 50 travels the Internet 90 and performs a crawling process of indexing information obtained from the website, web page and web content of the crawl destination into the index database, and HTTP including a search term from the searcher's computer Hyper Text Transfer Protocol) Request (search query) is received, and the website, web page, and web content title, URL (Uniform Resource Locator), and set of snippets (Snippet) related to the search term in the search query And a search process that returns search results arranged in order from the one with the highest ranking). Here, in the search processing, when the search engine server device 50 receives an HTTP request (order inquiry request) including the URL of the website, the web page, or the web content and the information indicating the past date and time, The order of the web site, web page, or web content is returned. Although only one search engine server device 50 is illustrated in FIG. 1, the number of search engine server devices 50 may be plural.

  The user terminal 10 is a personal computer. A unique ID and password are assigned to the user of the user terminal 10. The user accesses the evaluation device 20 from his / her user terminal 10 to perform an authentication procedure, and uses a service provided by the evaluation device 20. Although only one user terminal 10 is illustrated in FIG. 1, the number of user terminals 10 in the evaluation system 1 may be plural.

  The evaluation device 20 is a device that plays a role of providing a quantitative evaluation service for changes in rank over time. The quantitative evaluation service of the time change of the rank receives the search term from the user, and the search result based on the search term at the first time point before the current date and time (use date and time of the service) The ranking of each of the top web site, web page, and web content, and the top web site in the search result when the search is performed based on the search term at the second time point before the first time point, web It is a service for obtaining an index indicating correlation with the order of each page and web content, and presenting the index to the user as an analysis result specific to the search term.

  As shown in FIG. 1, the evaluation apparatus 20 includes a communication interface 21, a CPU (Central Processing Unit) 22, a RAM (Random Access Memory) 23, a ROM (Read Only Memory) 24, and a hard disk 25. The communication interface 21 transmits and receives data to and from devices connected to the Internet 90. The CPU 22 executes various programs stored in the ROM 24 and the hard disk 25 while using the RAM 23 as a work area. The ROM 24 stores an IPL (Initial Program Loader) and the like. The hard disk 25 stores an evaluation program 26 having functions specific to the present embodiment.

Next, the operation of this embodiment will be described.
FIG. 2 is a flow chart showing the flow of the evaluation method executed by the CPU 22 of the evaluation device 20 in accordance with the evaluation program 26. The CPU 22 functions as an input unit that executes an input process (step SA100) by executing the evaluation program 26, an acquisition unit that executes an acquisition process (step SA110), and an analysis unit that executes an analysis process (step SA120). To do.

  In the input process of step SA100 of FIG. 2, the CPU 22 transmits document data in which the structure of the input screen is described in HTML as shown in FIG. 3 to the user terminal 10 which has completed the authentication procedure. When the user terminal 10 receives this document data, it displays an input screen. On the input screen, a character string “Please enter a search term” is displayed. Below that, there is a search term input field 51. In the search word input field 51, a search word to be evaluated for the temporal change of the rank is input by the user. Below the search word input field 51, characters "Please specify the first date and time" are displayed. Below that, there is a date and time input field 52. In the date / time input field 52, date / time information indicating a date before the current date / time is input by the user as information indicating the first time point. The information in the date and time input field 52 may indicate the first time point by year, month and day, or may indicate the first time point by year, month, day and time. Under the date and time input field 52, a character string “Please specify the second date and time with a time difference” is displayed. Below that, there is a date and time input field 53. In the date / time input field 53, information indicating a time difference from the first time point is input by the user as information indicating the second time point. The information in the date and time input column 53 may indicate the time difference from the first time point on a daily basis, may indicate on a weekly basis, or may indicate on a monthly basis. Or it may be shown in units of years.

  Under the date and time input field 53, a character string “Please input the analysis range” is displayed. The analysis range is the search result in the case where the web search is performed with the search term input in the search term input field 51 at the date and time indicated by the date and time information input in the date and time entry field 52 (that is, the first time point). This means how many of the top web sites, web pages, and web content are to be analyzed. Below the character string “Please enter the analysis range”, there is an analysis range input field 54. In the analysis range input field 54, a number N (N is a natural number of 2 or more) indicating the analysis range is input by the user. The analysis range input field 54 may select one of a plurality of options, such as top 10, top 20 and top 30. Below the analysis range input field 54 is a send button 55.

  The user inputs a search term in the search term input field 51 of the input screen, inputs information indicating the first time point in the date and time input field 52, and the time difference between the first and second time points in the date and time input field 53 The number N indicating the analysis range is input to the analysis range input field 54, and the transmission button 55 is pressed. When the transmission button 55 is pressed, the user terminal 10 uses the information input in the search term input field 51, the date and time input field 52, the date and time input field 53, and the analysis range input field 54 as input information. It transmits to the evaluation apparatus 20. When the CPU 22 receives input information from the user terminal 10 via the Internet 90, the CPU 22 writes the received input information in the RAM 23.

Next, the CPU 22 executes an acquisition process (step SA110). As shown in FIG. 2, the acquisition process includes steps SA 110 a and SA 110 b. In step SA110a, the CPU 22 performs the search based on the search word in the input information at the first time point (date in the date / time input field 52), the top N-rank web site, web page, or web in the search result. Content is an analysis target, and the order of N web sites, web pages, or web contents to be analyzed is the search result data A _i at a first point in time (i = 1 to N, i represents the order in the search result) Index).

In step SA110b, the CPU 22 ranks N web sites, web pages, or web contents to be analyzed at a second time point (a date that is backed by the time difference in the date / time input field 53 from the date in the date / time input field 52). Are acquired as search result data B _i (i = 1 to N) at a second time point. Here, there may be a case where the web site, web page, or web content that was in the top N in the search result of the search at the first point in time is out of service in the search result of the search at the second point in time. Such web site, web page, or web content search result data _Bi may be a sufficiently large value (for example, 1000).

In the analysis process of step SA120, the CPU 22 indicates the order indicated by the search result data A _i (i = 1 to N) at the first time point and the search result data B _i (i = 1 to N) at the second time point. An index ρ (t, d) indicating the correlation between the two is obtained by applying the rank to the function of the following expression (1), and this index ρ (t, d) is analyzed peculiar to the search word in the input information. Output as a result.

Here, t in the formula (1) represents the first time point. d represents the time difference between the first time point and the second time point. Since the second time point is a time point before the first time point, the second time point is expressed as td. x (t) _i is an index associated with the search result data A _i in the table TBL 1 of the ROM 24. In the table TBL1, pairs of ranks and indices are stored. The indexes of the table TBL1 have larger values as they correspond to higher ranks. xm (t) is an average value (additional average) of indices x (t) _i corresponding to each of the search result data A _i (i = 1 to N). X (t−d) _i is an index associated with the search result data B _i in the table TBL1. xm (t−d) is an average value (addition average) of the indices x (t) _i corresponding to each of the search result data B _i (i = 1 to N).

  The acquisition process and the analysis process will be described in more detail. As shown in the example of FIG. 4, the CPU 22 determines that the information in the search term input field 51 of the input screen is “insurance” and the information in the date and time input field 52 is “2017.12. .12 ”, the information in the date and time input field 53 is“ one week ago ”, and the information in the analysis range input field 54 is“ 10 ”, at the time of December 12, 2017 (first time point) Perform a search based on the search term “insurance” and a search based on the same search term “insurance” as of December 5, 2017 one week ago (the second point in time) The top 10 web sites, web pages, and web content in the search results of the current search are targeted for analysis.

The CPU 22 sets the ranks of the 10 web sites, web pages, and web contents to be analyzed in the search results of the search as of December 12, 2017 as search result data A ₁ , A ₂ ... A _10. , The rankings of the 10 web sites, web pages, and web contents to be analyzed in the search results as of December 5, 2017 are the search result data B ₁ , B ₂ ... B ₁₀ . CPU22 from table TBL1 of ROM 24, the search result data _{A 1, A} 2 ··· _{A 10} and the corresponding index _{x (t) 1, x (} t) 2 ··· x (t) 10, and search result data _{B 1,} B 2 ··· B ₁₀ and the corresponding index _{x (t-d) 1,} x (t-d) taking out the _{2 ··· x (t-d)} 10. Further, the CPU 22 calculates the average xm (t) of the indices x (t) ₁ , x (t) ₂ ... X (t) ₁₀ , and the indices x (t−d) ₁ , x (t−d) _2. Determine the average xm (t−d) of x (t−d) ₁₀ .

Then, the CPU 22 uses the indices x (t) ₁ , x (t) ₂ ... X (t) ₁₀ , the average mx (t), and the indices x (td) ₁ , x (td). ₂ ... X (t-d) ₁₀ and the average xm (t-d) are input to the equation (1) to obtain an index ρ (t, d), and this index ρ (t, d) is obtained from the search term “ The analysis result specific to “insurance” is transmitted to the user terminal 10.

  The user of the user terminal 10 of the transmission source of the input information uses the index 時間 (t, d) returned from the evaluation device 20 to quantitatively evaluate the time change of the ranking of the web site etc. related to the commercial material of the user. And understand the characteristics of the market of their own material. For example, an index ((t, d) calculated by the evaluation device 20 by specifying each of tn = t0−n × d (n = 0 to 10) as the first time point t when the current date and time is t0. Is always close to 1 as shown in the graph (A) in FIG. The fact that the value of the index ((t, d) is close to 1 means that the top position of the search results is considered to have not changed so much over the period from time t10 to t0, and it is a market where information freshness is not required It can be estimated. On the contrary, as shown in the graph (B) in FIG. 5, if the index ((t, d) is always a small value of 0.5 or less, the upper part of the search result is constantly changing It can be estimated that the market is required to have freshness of information.

  Further, if the index ((t, d) changes periodically as shown by the graph (C) in FIG. 5, it can be estimated that the market is seasonal. In this case, by obtaining the span of the cycle of the index ρ (t, d), it is possible to estimate in what unit (month, quarter, half year, etc.) the market is changing. Further, by comparing the time changes of the index ρ (t, d) calculated for each of a plurality of different search terms, the time change of the rank due to the change of the search algorithm in the search engine server device 50 can be obtained. It is possible to estimate if there is a time change specific to a search term. For example, in the graph (D) and the graph (E) in FIG. 5, the index ρ calculated for each of the search term X, the search term Y, and the search term Z, which are different search terms, in the period of time t10 to t0. The graph curves of t and d) are drawn by a solid line, a dotted line, and an alternate long and short dash line. In the graph (D) in FIG. 5, the value of the index ((t, d) drops sharply at time t6 for all of the search term X, the search term Y and the search term Z. This means that for all the search terms X, search terms Y, and search terms Z at the time point t6, the upper rank of the search result has largely changed, and the search algorithm is between the time point t5 and the time point t6 It is estimated that changes were made. On the other hand, in the graph (E) in FIG. 5, a sharp drop of the value of the index ((t, d) occurs only for the search word Y, which is a time change specific to the search word Y It is estimated to be.

  As described above, according to the evaluation device 20 of the present embodiment, it is possible to quantitatively evaluate how the upper rank of the search result of the search word changes as time passes. Therefore, according to the present embodiment, a company performing SEO or marketing distinguishes between a material field that is required to be more responsive to changes in current trends and a non-sale material field, and performs more realistic resource allocation. be able to.

Second Embodiment
FIG. 6 is a diagram showing an overall configuration of an evaluation system 1A including an evaluation apparatus 20A that is the second embodiment of the present invention. The evaluation system 1A is a high-ranked search result in the case where a search term based on a certain search word is selected from the document data group collected from the user terminal 10 in the company LAN (Local Area Network) 80 to the document management server device 30. Quantitatively evaluate how it changes with the passage of time.

  In FIG. 6, the user terminal 10 and the evaluation device 20 </ b> A of the evaluation system 1 </ b> A are connected to the document management server device 30 via the LAN 80. The document management server device 30 is a device that plays a role of providing a document management service. The document management server device 30 receives document data from the user terminal 10 in the LAN 80, stores the received document data in the document database 31, receives a search query from the user terminal 10, and receives a search query Search processing for searching the document database 31 for document data relating to the search term of the document, and arranging the title, URL, and snippet of the searched document data in order from the top (higher rank) set And do.

The evaluation device 20A of the evaluation system 1A executes the input process, the acquisition process, and the analysis process shown in FIG. 2 by the function of the evaluation program 26 in the hard disk 25. The contents of these processes are such that the acquisition destination of the search result data A _i (i = 1 to N) at the first time point and the search result data B _i (i = 1 to N) at the second time point is the document management server device. The third embodiment is the same as the first embodiment except that the thirty document databases 31 are included. According to this embodiment, the same effect as that of the first embodiment can be obtained.

Third Embodiment
FIG. 7 is a diagram showing an overall configuration of an evaluation system 1B including an evaluation apparatus 20B that is the third embodiment of the present invention. Similar to the evaluation system 1 of the first embodiment, the evaluation system 1C shows how the upper rank of the search result is as time elapses when a search is performed based on a search word from a group of document data scattered on the Internet 90. It is a quantitative evaluation of whether it is changing.

  In FIG. 7, the user terminal 10 and the evaluation device 20 </ b> A of the evaluation system 1 </ b> A are connected to the search result collection server device 40 via the LAN 80. The search result collection server device 40 is a device that plays a role of providing a search result collection service. The search result collection server device 40 transmits search queries for various search terms to the search engine server device 50 and receives search results from the search engine server device 50 at predetermined time intervals (for example, every 10 minutes). Then, a process of accumulating a set of search terms, search date and time, and search results in the search result database 41 is performed.

The evaluation device 20B of the evaluation system 1B executes the input process, the acquisition process, and the analysis process shown in FIG. 2 by the function of the evaluation program 26 in the hard disk 25. The content of these processes is that the search result data A _i (i = 1 to N) at the first time point and the search result data B _i (i = 1 to N) at the second time point are acquired from the search result collection server. Except for the search result database 41 of the apparatus 40, the second embodiment is the same as the first embodiment. According to this embodiment, the same effect as the first and second embodiments can be obtained.

Fourth Embodiment
FIG. 8 is a diagram showing an overall configuration of an evaluation system 1C including an evaluation apparatus 20C that is the fourth embodiment of the present invention. Similar to the evaluation system 1 of the first embodiment, the evaluation system 1C shows how the upper rank of the search result is as time elapses when a search is performed based on a search word from a group of document data scattered on the Internet 90. It is a quantitative evaluation of whether it is changing.

  In FIG. 8, a search engine server device 50 and an access analysis server device 60 are connected to the Internet 90. The access analysis server device 60 is a device that plays a role of providing an access analysis service. The access analysis server device 60 receives, from the user terminal 10, an HTTP request including the URL of the document data subject to access analysis on the Internet 90, and click through rate, stay time and withdrawal rate of the URL of the document data subject to access analysis. , Information such as the number of inflows and the number of browsing pages are returned as the access analysis result. Here, when the access analysis server device 60 receives an HTTP request including the URL of the document data to be accessed and the information indicating the past date and time, the access analysis server device 60 sends back the access analysis result at the relevant date and time.

  The evaluation device 20C of the evaluation system 1C executes the input processing, the acquisition processing, and the analysis processing shown in FIG. 2 by the operation of the evaluation program 26 in the hard disk 25. Among these processes, the content of the input process is the same as that of the first embodiment.

In the present embodiment, in the acquisition process, the CPU 22 of the evaluation device 20C determines the top N search results in the search result based on the search term in the input information at the first time point (the date in the date and time input field 52). Web site, web page, or web content is analyzed, the click-through rate of N web sites, web pages, or web content to be analyzed is acquired from the access analysis server device 60, and these click-through rates are obtained. It is assumed that the access analysis data C _i (i = 1 to N) of the access destination in the search result of the search at the first time point. In addition, the CPU 22 clicks through N web sites, web pages, or web contents to be analyzed at a second time point (date that is backed by the time difference in the date / time input field 53 from the date in the date / time input field 52). Are obtained from the access analysis server device 60, and these click-through rates are set as access analysis data D _i (i = 1 to N) of the access destination in the search result of the search at the second time point.

In the analysis processing, the CPU 22 clicks the click-through rate indicated by the first time access analysis data C _i (i = 1 to N) and the second time access analysis data D _i (i = 1 to N). By causing the slew rate to act on the function of the above equation (1), an index ρ (t, d) indicating the correlation between the two is obtained, and this index ρ (t, d) is specific to the search term in the input information. Output as analysis result.

  The acquisition process and analysis process of the present embodiment will be described in more detail. As shown in the example of FIG. 9, the CPU 22 determines that the information in the search term input field 51 of the input screen is “insurance”. If the information is “2017.12.12”, the information in the date / time input field 53 is “one week ago”, and the information in the analysis range input field 54 is “10”, the time as of December 12, 2017 (first The search based on the search term “insurance” at time point) and the search based on the same search term “insurance” as of December 5, 2017 one week ago (second time point) The top 10 web sites, web pages, and web content in the search results of the search as of the 12th of March are targeted for analysis.

The CPU 22 analyzes the 10 websites, web pages, and click-through rates of web contents in the search results of the search as of December 12, 2017. Access analysis data C ₁ , C ₂ ... C ₁₀ and the click-through rates of the 10 web sites, web pages, and web contents to be analyzed in the search results as of December 5, 2017 are the access analysis data D ₁ , D ₂ ... D ₁₀ And The CPU 22 determines from the table TBL2 of the ROM 24 the access analysis data C ₁ , C ₂ ... C ₁₀ and the corresponding indices x (t) ₁ , x (t) ₂ ... X (t) ₁₀ and the access analysis data _{D 1,} D 2 ··· D ₁₀ and corresponding indicator _{x (t-d) 1,} x (t-d) taking out the _{2 ··· x (t-d)} 10. Further, the CPU 22 calculates the average xm (t) of the indices x (t) ₁ , x (t) ₂ ... X (t) ₁₀ , and the indices x (t−d) ₁ , x (t−d) _2. Determine the average xm (t−d) of x (t−d) ₁₀ .

Then, the CPU 22 uses the indices x (t) ₁ , x (t) ₂ ... X (t) ₁₀ , the average mx (t), and the indices x (td) ₁ , x (td). ₂ ... X (t-d) ₁₀ and the average xm (t-d) are input to the equation (1) to obtain an index ρ (t, d), and this index ρ (t, d) is obtained from the search term “ An analysis result unique to “insurance” is transmitted to the user terminal 10. According to the present embodiment, the same effects as in the first to third embodiments can be obtained.

Fifth Embodiment
FIG. 10 is a diagram showing an overall configuration of an evaluation system 1D including an evaluation apparatus 20D that is the fifth embodiment of the present invention. In FIG. 10, the user terminal 10 and the evaluation device 20 </ b> D of the evaluation system 1 </ b> D are connected to the document management server device 30 via the LAN 80. The document management server device 30 receives, from the user terminal 10, a request including the address of the storage destination of the document data to be subjected to access analysis in the document database 31, and click-through rate, stay time, and departure of document data to be accessed. Information such as the rate, the number of inflows, and the number of browsing pages is returned as the access analysis result.

The evaluation device 20D of the evaluation system 1D executes the input process, the acquisition process, and the analysis process shown in FIG. 2 by the function of the evaluation program 26 in the hard disk 25. The contents of these processes are such that the acquisition destination of the access analysis data C _i (i = 1 to N) at the first time point and the access analysis data D _i (i = 1 to N) at the second time point is the document management server device. The fourth embodiment is the same as the fourth embodiment except that the thirty document databases 31 are used. According to the present embodiment, the same effects as in the first to fourth embodiments can be obtained.

Sixth Embodiment
FIG. 11 is a diagram showing an overall configuration of an evaluation system 1E including an evaluation apparatus 20E that is the sixth embodiment of the present invention. In FIG. 11, the user terminal 10 and the evaluation device 20E of the evaluation system 1E are connected to the access analysis result collection server device 45 via the LAN 80.

  The access analysis result collection server device 45 is a device that plays a role of providing an access analysis result collection service. The access analysis result collection server device 45 transmits HTTP requests including URLs of various document data to the access analysis server device 60 at predetermined time intervals (for example, every 10 minutes), and accesses from the access analysis server device 60. A process of receiving analysis results (information such as click through rate, staying time, withdrawal rate, number of inflows, number of viewed pages, etc.), and storing a set of URL of document data, analysis date, and analysis result in access analysis result database 46 I do.

The evaluation device 20E of the evaluation system 1E executes the input process, the acquisition process, and the analysis process shown in FIG. 2 by the function of the evaluation program 26 in the hard disk 25. The contents of these processes are as follows: the access analysis data C _i (i = 1 to N) at the first time point and the access analysis data D _i (i = 1 to N) at the second time point are collected by the access analysis result. The fourth embodiment is the same as the fourth embodiment except that it is the access analysis result database 46 of the server device 45. According to the present embodiment, the same effects as in the first to fifth embodiments can be obtained.

<Modification>
Although the first to sixth embodiments of the present invention have been described above, the following modification may be added to this embodiment.

(1) In the first to third embodiments, the CPU 22 of the evaluation devices 20, 20A, 20B processes N document data (web) to be analyzed at the first time point in the acquisition process (step SA110 in FIG. 2). The order of the site, web page or web content is acquired as search result data A _i (i = 1 to N) at the first point of time, and the order of the N document data to be analyzed at the second point of time is It was obtained as a search result of the second time point data _B i (i = _1~N). However, snippet analysis data obtained by performing predetermined analysis processing on the snippets of N document data to be analyzed at the first time point is acquired as search result data A _i (i = 1 to N) at the first time point And obtains snippet analysis data obtained by performing predetermined analysis processing on the snippets of N document data to be analyzed at the second time point as search result data B _i (i = 1 to N) at the second time point May be. As shown in the example of FIG. 12, in this modification, in the analysis process, the table TBL3 in which the snippet analysis data in the ROM 24 is associated with the index is referred to, and the search result data A _{i is} converted to the index x (t) _i . It is preferable that conversion and conversion of search result data B _i into index x (t−d) _i be performed. The contents of the input process, the acquisition process, and the analysis process in this modified example are the first to the first except that the snippet analysis data at the first time point and the second time point are the search result data A _i and B _i . It may be the same as in the third embodiment.

(2) In the fourth to sixth embodiments, the CPU 22 of the evaluation devices 20C, 20D, and 20E determines N pieces of document data (web) to be analyzed at the first time point in the acquisition process (step SA110 in FIG. 2). The click-through rate of the URL of the site, web page, or web content) is acquired as access analysis data C _i (i = 1 to N) at the first time point, and N pieces of document data to be analyzed at the second time point the URL for click Sioux rate obtained as the second time access analysis data _D i (i = _1~N). However, the stay time in the URL of the N document data to be analyzed at the first time is acquired as the access analysis data C _i (i = 1 to N) at the first time, and the analysis target at the second time is acquired. of N residence time in the URL of the document data may be acquired as the second time access analysis data _D i (i = _1~N). As shown in the example of FIG. 13, in this modified example, in the analysis process, the table TBL4 in which the stay time in the ROM 24 is associated with the index is referred to, and the access analysis data C _i is converted into the index x (t) _i . And conversion of the access analysis data D _i into the index x (t−d) _i may be performed. The contents of the input process, the acquisition process, and the analysis process in this modified example are the fourth to sixth except that the stay times at the first time point and the second time point are the access analysis data C _i and D _i . It may be similar to the embodiment.

(3) In the fourth to sixth embodiments, the CPU 22 of the evaluation devices 20C, 20D, and 20E determines N pieces of document data (web) to be analyzed at the first time point in the acquisition process (step SA110 in FIG. 2). The click-through rate of the URL of the site, web page, or web content) is acquired as access analysis data C _i (i = 1 to N) at the first time point, and N pieces of document data to be analyzed at the second time point the URL for click-through rate obtained as the second time access analysis data _D i (i = _1~N). However, the withdrawal rate in the URL of the N document data to be analyzed at the first time point is acquired as the access analysis data C _i (i = 1 to N) at the first time point, and the analysis target at the second time point is analyzed. The withdrawal rate at the URL of N document data may be acquired as access analysis data D _i (i = 1 to N) at the second time point. As shown in the example of FIG. 14, in this modification, in the analysis process, the table TBL5 in which the withdrawal rate in the ROM 24 is associated with the index is referred to, and the access analysis data C _i is converted into the index x (t) _i . And conversion of the access analysis data D _i into the index x (t−d) _i may be performed. The contents of the input process, the acquisition process, and the analysis process in this modification are the fourth to the sixth except that the withdrawal rates at the first and second points are taken as the access analysis data C _i and D _i . It may be similar to the embodiment.

(4) In the fourth to sixth embodiments, the CPU 22 of the evaluation devices 20C, 20D, and 20E performs N document data (web) to be analyzed at the first time point in the acquisition process (step SA110 in FIG. 2). The click-through rate of the URL of the site, web page, or web content) is acquired as access analysis data C _i (i = 1 to N) at the first time point, and N pieces of document data to be analyzed at the second time point the URL for click-through rate obtained as the second time access analysis data _D i (i = _1~N). However, the inflow number in the URL of the N document data to be analyzed at the first time point is acquired as the access analysis data C _i (i = 1 to N) at the first time point, and the analysis target object at the second time point is obtained. The number of inflows in the URL of N document data may be acquired as the access analysis data D _i (i = 1 to N) at the second time point. As shown in the example of FIG. 15, in this modification, in the analysis process, the table TBL6 in which the number of inflows in the ROM 24 is associated with the index is referred to, and the access analysis data C _i is converted into the index x (t) _i . And conversion of the access analysis data D _i into the index x (t−d) _i may be performed. The contents of the input process, the acquisition process, and the analysis process in this modification are the fourth to sixth except that the inflow numbers at the first time point and the second time point are the access analysis data C _i and D _i . It may be similar to the embodiment.

(5) In the fourth to sixth embodiments, the CPU 22 of the evaluation devices 20C, 20D, and 20E causes the N pieces of document data (web) to be analyzed at the first time point in the acquisition process (step SA110 in FIG. 2). The click-through rate of the URL of the site, web page or web content is acquired as access analysis data C _i (i = 1 to N) at the first point of time, and N document data to be analyzed at the second point of time the URL for click-through rate obtained as the second time access analysis data _D i (i = _1~N). However, the number of browsed pages of N document data to be analyzed at the first time point is acquired as access analysis data C _i (i = 1 to N) at the first time point, and N to be analyzed at the second time point. The number of browsing pages of individual document data may be acquired as the access analysis data D _i (i = 1 to N) at the second time point. As shown in the example of FIG. 16, in this modification, in the analysis process, the table TBL6 in which the number of browse pages in the ROM 24 is associated with the index is referred to, and the access analysis data C _{i is} converted to the index x (t) _i . It is preferable that conversion and conversion of access analysis data D _i into index x (t−d) _i be performed. Input processing in this modified example, the contents of the acquisition process, and analysis processing, except for the pages viewed in the first and second time points with access analysis data C _i and D _i, fourth to It may be the same as in the sixth embodiment.

(6) In the first to third embodiments, the order itself of the N document data to be analyzed at the first time point is set as an index x (t) _i (i = 1 to N) based on the order. The rank itself of the N pieces of document data to be analyzed at the second time point may be an index x (t−d) _i (i = 1 to N) based on the rank. Similarly, when the snippet analysis data is used as the search result data B _i and A _i , the snippet analysis data itself at the first time point and the second time point of the N pieces of document data is used as an index x based on the snippet analysis data. (T) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) may be used.

In addition, the number of the document data to be analyzed at the first time point converted into rank (log) or reciprocal (1 / rank) of the rank of the document data to be analyzed is an index x (t) _i (i = 1 to 6) based on the rank. N), and a number obtained by converting the rank of the N pieces of document data to be analyzed at the second time point into a logarithm (log) or a reciprocal (1 / rank), an index x (t−d) _i ( i = 1 to N). Similarly, when the snippet analysis data is set as the search result data A _i and B _i , the snippet analysis data at the first time point and the second time point of the N document data are similarly expressed by logarithm (log) or reciprocal (1 / snippet analysis). The number converted into (data) may be used as indices x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) based on the snippet analysis data.

Further, the number of N document data to be analyzed at the first time point multiplied by N weighting factors is set as an index x (t) _i (i = 1 to N) based on the order, and A number obtained by multiplying the order of N document data to be analyzed at time 2 by N weighting factors may be used as an index x (t−d) _i (i = 1 to N) based on the order. In this case, the higher the ranking, the higher the weighting factor, or the higher the ranking, the lower the weighting factor. Similarly, when the snippet analysis data is set as the search result data A _i and B _i , similarly, the number obtained by multiplying the snippet analysis data at the first time point and the second time point of the N document data by the N weighting factors, The indices x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) based on the snippet analysis data may be used.

(7) In the fourth to sixth embodiments, the click through rate itself of the N document data to be analyzed at the first time point is an index x (t) _i (i = 1 to 1) based on the click through rate. N), and the click through rate itself of the N pieces of document data to be analyzed at the second time point may be an index x (t−d) _i (i = 1 to N) based on the click through rate. Similarly, when the stay times are the access analysis data C _i and D _i , the stay times at the first time point and the second time point of the N pieces of document data are used as indices x (t) based on the stay time. _It may be _i (i = 1 to N) and x (t−d) _i (i = 1 to N). Similarly, in the case where the withdrawal rate is the access analysis data C _i and D _i , the withdrawal rate itself of the first time point and the second time point of the N document data is used as an index x (t) based on the withdrawal rate. _It may be _i (i = 1 to N) and x (t−d) _i (i = 1 to N). Similarly, in the case where the inflow number is the access analysis data C _i and D _i , the inflow number itself of the first time point and the second time point of the N document data is an index x (t) based on the inflow number. _It may be _i (i = 1 to N) and x (t−d) _i (i = 1 to N). Similarly, when the number of browsing pages is set as the access analysis data C _i and D _i , similarly, the number x of the browsing pages at the first time point and the second time point of the N pieces of document data is used as an index x based on the number of browsing pages. (T) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) may be used.

In addition, the index x (t) based on the click-through rate is the number obtained by converting the click-through rate of N document data to be analyzed at the first time point into a logarithm (log) or reciprocal (1 / click-through rate). _i (i = 1 to N), and the click-through rate of N document data to be analyzed at the second time point is converted to the logarithm (log) or reciprocal (1 / click-through rate) by the click-through rate It may be an index x (t−d) _i (i = 1 to N) based on a rate. Similarly, when the stay times are the access analysis data C _i and D _i , the stay times at the first time point and the second time point of the N document data are logarithmically (log) or reciprocal (1 / stay time). The converted numbers may be indices x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) based on the stay time. Similarly, in the case where the withdrawal rate is the access analysis data C _i and D _i , the withdrawal rates of the first and second time points of the N document data are made logarithmic (log) or inverse (1 / deletion rate) The converted numbers may be used as indices x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) based on the departure rate. Similarly, in the case where the number of inflows is the access analysis data C _i and D _i , the number of inflows at the first time point and the second time point of N document data is made logarithmic (log) or reciprocal (1 / inflow number) The converted numbers may be indices x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) based on the number of inflows. Similarly, when the number of browsing pages is set as the access analysis data C _i and D _i , similarly, the number of browsing pages at the first time point and the second time point of the N document data is expressed by logarithm (log) or reciprocal (1 / viewing page). The number converted into (number) may be an index x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) based on the number of browsed pages.

In addition, the click-through rate of the N document data to be analyzed at the first time point multiplied by N weighting factors is the index x (t) _i (i = 1 to N) based on the click-through rate. The click-through rate of the N document data to be analyzed at the second time point multiplied by N weighting factors is the index x (t−d) _i (i = 1) based on the click-through rate To N). In this case, the higher the click-through rate, the higher the weighting factor, or the higher the click-through rate, the lower the weighting factor. Similarly, when the stay time is set as the access analysis data C _i and D _i , similarly, the number obtained by multiplying the stay time at the first time point and the second time point of the N document data by the N weighting coefficients is used. Indexes based on time x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) may be used. Also in the case where the withdrawal rate is the access analysis data C _i and D _i , similarly, the number obtained by multiplying the withdrawal rates of the first and second time points of N document data by N weighting factors is The index x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) based on the rate may be used. Similarly, in the case where the number of inflows is the access analysis data C _i and D _i , the number obtained by multiplying the number of inflows at the first time point and the second time point of N document data by N weighting factors is Indexes based on numbers x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) may be used. Similarly, when the number of browsing pages is set as the access analysis data C _i and D _i , similarly, the number obtained by multiplying the number of browsing pages at the first time point and the second time point of the N document data by N weighting factors, The index x (t) _i (i = 1 to N) and x (t−d) _i (i = 1 to N) based on the number of browsed pages may be used.

(8) In the first to sixth embodiments, the first time point is specified by date and time, and the second time point is specified by time difference from the first time point. However, the second time point may be designated by date and time. Further, if the second time point is determined as “a time point one week before the first time point”, the second time point does not need to be specified by the user, and the first time point is set to the “current date and time”. It is not necessary to let the user specify the first time point. In other words, it is not essential for the user to designate the first and second points in time, and it is sufficient that the user designate at least one even if he / she designates the first and second points in time.

(9) In the first to sixth embodiments, the evaluation systems 1, 1A, 1B, 1C, 1D, 1E including the evaluation devices 20, 20A, 20B, 20C, 20D, 20E have been described. 20A, 20B, 20C, 20D, and 20E may be manufactured and sold alone. Further, in the above embodiment, by operating the CPU 22 according to the evaluation program 26, the CPU 22 is caused to execute the evaluation method that shows the features of the present invention. However, each of the input means for executing the input process, the acquisition means for performing the acquisition process, and the analysis means for performing the analysis process is constituted by an electric circuit, and these respective means are combined to evaluate the evaluation devices 20, 20A,. 20B, 20C, 20D, and 20E may be configured.

(10) In the first to sixth embodiments, the evaluation program 26 which causes the CPU 22 to execute the evaluation method which shows the features of the present invention remarkably is previously stored in the hard disk 25 of the evaluation apparatus 20, 20A, 20B, 20C, 20D, 20E. It was remembered. However, the evaluation program 26 may be distributed by writing the evaluation program 26 on a computer readable recording medium such as a DVD (Digital Versatile Disc) or a USB (Universal Serial Bus) memory, or the evaluation program by downloading via a telecommunication line such as the Internet. 26 may be distributed. By operating a general computer according to the evaluation program 26 distributed in this manner, it becomes possible to cause the computer to function as the evaluation device 20, 20A, 20B, 20C, 20D, 20E of the present invention.

(11) In the first to sixth embodiments, not only ρ (t, d) in one search word but also changes in ρ (t, d) of many other search words are changed. It is also possible to estimate whether it is due to a search engine algorithm or a time-series change that is unique to the search term. The search term referred to here conceptually includes a so-called second word, and it becomes possible to grasp changes in the appearance frequency in the process of the above estimation.

(12) In the first to sixth embodiments, the time t and the time difference d are exemplified in FIG. 4 and only the case where d is a constant is shown, but the time t is a constant and the time difference d is a variable Of course, the versatility may be enhanced by using the time t and the time difference d as variables. An example of display when time t and time difference d are variables is shown in FIG. A histogram-like diagram as shown in the figure may be presented to the user, and may be used for general market analysis or company analysis for a market or company changing on its own time.

1, 1A, 1B, 1C, 1D, 1E ... evaluation system, 10 ... user terminal, 20, 20A, 20B, 20C, 20D, 20E ... evaluation device, 21 ... communication interface, 22 ... CPU, 23 ... RAM, 24 ... ROM, 25 ... hard disk, 26 ... evaluation program, 30 ... document management server device, 40 ... search result collection server device, 45 ... access analysis result collection server device, 50 ... search engine server device, 60 ... access analysis server device.

Claims (22)

An input means for inputting a search term;
An acquisition means for acquiring search result data based on the search word at a first time point and acquiring search result data based on the search word at a second time point different from the first time point;
An analysis means for obtaining an index indicating a correlation between the search result data at the first time point and the search result data at the second time point, and outputting the index as an analysis result specific to the search word. Search term evaluation device.   The evaluation apparatus according to claim 1, further comprising a specifying unit that specifies at least one of the first time point and the second time point. The search result data includes N (N is a natural number of 2 or more natural number) document data ranked high in the search result when a search based on the search term is performed among document data groups described in a markup language. Ranking,
The analysis means operates the index indicating the correlation by applying an order of the N document data at the first time and an order of the N document data at the second time to a predetermined function. The evaluation device according to claim 2, wherein the evaluation device is obtained. The second point in time is a point in time earlier than the first point in time,
The analysis means includes
The time difference between the first time point t and the second time point is d, and an index based on the order or order of the i th document data of the N document data at the first time point t is x (t ) _i, the average value of the index xm (t), the index ranking based on rank or order of the i-th document data among the N document data in the second time point t-d x (t- d) _i, the average value of the index when the xm (t-d), characterized in that said determining the index indicating the correlation [rho (t, d) according to the function shown in the following equation (1) The evaluation apparatus according to claim 3.
The search result data includes N (N is a natural number of 2 or more natural number) document data ranked high in the search result when a search based on the search term is performed among document data groups described in a markup language. This is snippet analysis data obtained by applying a predetermined analysis process to the snippet.
The analysis means obtains an index indicating the correlation by applying the N snippet analysis data at the first time point and the N snippet analysis data at the second time point to a predetermined function. The analyzer according to claim 2, characterized in that The second point in time is a point in time earlier than the first point in time,
The analysis means includes
The time difference between the first time point t and the second time point is d, and the index is based on the snippet analysis data or the snippet analysis data of the i-th document data in the N document data at the first time point t. X (t) _i , the average value of the index is xm (t), and the snippet analysis data or snippet analysis data of the i-th document data in the N document data at the second time point t-d When the index based on x is (t-d) _i and the average value of the index is xm (t-d), the index 示 す (t, d) indicating the correlation according to the function shown in the following equation (1) The evaluation apparatus according to claim 5, wherein:
A user terminal and an evaluation device in communication with the user terminal;
The evaluation device is
An input means for inputting a search term;
An acquisition means for acquiring search result data based on the search word at a first time point and acquiring search result data based on the search word at a second time point different from the first time point;
Analysis means for obtaining an index indicating a correlation between the search result data at the first time point and the search result data at the second time point, and outputting the index as an analysis result unique to the search word. A search word evaluation system. An input step in which a search term is input;
Acquiring search result data of a search based on the search term at a first time, and acquiring search result data of a search based on the search term at a second time different from the first time;
An analysis step of obtaining an index indicating a correlation between the search result data at the first time point and the search result data at the second time point, and outputting the index as an analysis result unique to the search word. The evaluation method of the search term. An input means for inputting a search term;
Access analysis data of the access destination in the search result based on the search word at the first time point is acquired, and within the search result based on the search word at the second time point different from the first time point Acquisition means for acquiring the access analysis data of the access destination of
Analyzing means for obtaining an index indicating a correlation between the access analysis data at the first time point and the access analysis data at the second time point, and outputting the index as an analysis result unique to the search term. Search term evaluation device.   The evaluation apparatus according to claim 9, further comprising a specifying unit that specifies at least one of the first time point and the second time point. The access analysis data includes N (where N is 2 or more) that has a higher click-through rate at the address of document data in a search result when a search is performed based on the search word from a group of document data described in a markup language. Is the click-through rate of the document data)
The analyzing means applies the click-through rate of the N document data at the first time point and the click-through rate of the N document data at the second time point to a predetermined function, thereby causing the correlation to occur. The evaluation device according to claim 10, wherein an indicator indicating The second point in time is a point in time earlier than the first point in time,
The analysis means includes
The time difference between the first time point t and the second time point is d, and the click through rate of the N document data at the first time point t is the click through rate or click through rate of the i-th document data The index based on x (t) _i , the average value of the index is xm (t), and the click through rate of the N pieces of document data at the second time point t−d is the click through rate of the i th document data Or an index based on the click-through rate x (t-d) _i , and the average value of the index is xm (t-d), the index 示 す indicating the correlation according to the function shown in the following equation (1) The evaluation apparatus according to claim 11, wherein (t, d) is obtained.
In the access analysis data, N (where N is 2 or more), the staying time in the address of the document data in the search result when the search based on the search term is performed from the document data group described in the markup language This is the residence time of (natural number) pieces of document data,
The analysis means indicates the correlation by applying a stay time of the N document data at the first time and a stay time of the N document data at the second time on a predetermined function. The evaluation apparatus according to claim 10, wherein an index is obtained. The second point in time is a point in time earlier than the first point in time,
The analysis means includes
The time difference between the first time point t and the second time point is d, and the staying time of the N document data at the first time point t is an index based on the staying time or staying time of the i-th document data x (t) _i , the average value of the index is xm (t), and the stay time of the N document data at the second time point t-d is based on the stay time or stay time of the i-th document data Assuming that the index is x (t−d) _i and the average value of the index is xm (t−d), the index ((t, d) indicating the correlation according to the function shown in the following equation (1) The evaluation device according to claim 13, wherein the evaluation device is obtained.
The access analysis data includes N (where N is 2 or more) that has a higher leaving rate at the address of the document data in the search result when a search based on the search word is performed from the document data group described in the markup language. Natural number) leaving rate of individual document data,
The analysis means indicates the correlation by operating a separation rate of the N document data at the first time point and a separation rate of the N document data at the second time point on a predetermined function. The evaluation device according to claim 10, wherein an index is determined. The second point in time is a point in time earlier than the first point in time,
The analysis means includes
The time difference between the first time point t and the second time point is d, and the withdrawal rate of the N document data at the first time point t is an index based on the withdrawal rate or withdrawal rate of the i-th document data x (t) _i , the average value of the index is xm (t), and the withdrawal rate of the N pieces of document data at the second time point t-d is based on the withdrawal rate or the withdrawal rate of the i-th document data Assuming that the index is x (t−d) _i and the average value of the index is xm (t−d), the index ((t, d) indicating the correlation according to the function shown in the following equation (1) The evaluation device according to claim 15, wherein the evaluation device is obtained.
In the access analysis data, the number of inflows at the address of the document data in the search result when the search is performed based on the search word from the document data group described in the markup language (N is 2 or more) Natural number) is the number of document data inflows
The analysis means indicates the correlation by operating the inflow number of the N document data at the first time point and the inflow number of the N document data at the second time point on a predetermined function. The evaluation device according to claim 10, wherein an index is determined. The second point in time is a point in time earlier than the first point in time,
The analysis means includes
The time difference between the first time point t and the second time point is d, and the inflow number of the N document data at the first time point t is an index based on the inflow number or inflow number of the i-th document data x (t) _i , the average value of the index is xm (t), and the inflow number of the N pieces of document data at the second time t-d is based on the inflow number or the inflow number of the i-th document data Assuming that the index is x (t−d) _i and the average value of the index is xm (t−d), the index ((t, d) indicating the correlation according to the function shown in the following equation (1) The evaluation device according to claim 17, wherein the evaluation device is obtained.
The access analysis data is N (N is a natural number of 2 or more natural numbers) in which the number of browsing pages of document data in the search result in the case where a search based on the search term is performed from the document data group described in the markup language This is the number of browsing pages of document data,
The analysis means causes the correlation by causing the number of browsing pages of the N document data at the first time and the number of browsing pages of the N document data at the second time to act on a predetermined function. The evaluation device according to claim 10, wherein an indicator indicating The second point in time is a point in time earlier than the first point in time,
The analysis means includes
The time difference between the first time point t and the second time point is d, and the number of browsing pages of the N document data at the first time point t is the number of browsing pages or the number of browsing pages of the i-th document data The index based on x (t) _i , the average value of the index is xm (t), and the number of browsing pages of the N document data at the second time t-d is the number of browsing pages of the i-th document data Alternatively, when the index based on the number of browsed pages is x (t−d) _i and the average value of the index is xm (t−d), the index ρ indicating the correlation according to the function shown in the following formula (1) 20. The evaluation apparatus according to claim 19, wherein (t, d) is determined.
A user terminal and an evaluation device in communication with the user terminal;
The evaluation device is
An input means for inputting a search term;
Access analysis data of the access destination in the search result based on the search word at the first time point is acquired, and within the search result based on the search word at the second time point different from the first time point Acquisition means for acquiring the access analysis data of the access destination of
Analyzing means for obtaining an index indicating a correlation between the access analysis data at the first time point and the access analysis data at the second time point, and outputting the index as an analysis result unique to the search term. A search word evaluation system. An input step where the search term is entered;
Access analysis data of the access destination in the search result based on the search word at the first time point is acquired, and within the search result based on the search word at the second time point different from the first time point Acquisition step of acquiring access analysis data of the access destination of
An analysis step of obtaining an index indicating a correlation between the access analysis data at the first time point and the access analysis data at the second time point, and outputting the index as an analysis result unique to the search term. The evaluation method of the search term.