A special service system for paleontological fossil standard database

Abstract

The present invention discloses a paleontological fossil standard database special service system, relating to the field of electronic digital data processing technology. The paleontological fossil standard database special service system includes: an information input module, a feature extraction module, an image processing module, and a retrieval output module. The present invention analyzes the integrity of the fossil region based on the fossil retrieval image and determines whether to perform fossil retrieval image feature extraction. After performing the fossil retrieval image feature extraction, the present invention analyzes whether to perform fossil retrieval image processing adjustment. After the fossil retrieval image processing adjustment, the present invention performs a search based on the obtained fossil retrieval image features and the retrieval text to obtain retrieval information, thereby analyzing the retrieval information and determining whether to output the retrieval information. This improves the retrieval effectiveness of the paleontological fossil standard database and solves the problem of inaccurate retrieval results provided by the paleontological fossil standard database in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of electric digital data processing, in particular to a paleontological fossil standard database special service system. Background Art

[0002] Paleontology, a key discipline studying the evolutionary history of life on Earth, relies primarily on fossils for its research data. However, the diverse and vast number of paleontological fossils, along with their widespread distribution, pose significant challenges to the management, query, and utilization of these data. Traditional fossil data management relies primarily on paper documents and physical specimens, resulting in low retrieval efficiency and difficulties in information sharing. With the rapid development of computer and information technologies, database technology has become a crucial tool for fossil data management. The Paleontological Fossil Standard Database Service System was developed to address this challenge. Leveraging advanced database technology, it enables digital storage, management, and query of fossil data, significantly improving their utilization and sharing.

[0003] Significant progress has been made in the development of standard paleontological fossil databases and thematic service systems. For example, the Standard Paleontological Fossil Database and thematic service system developed by the Institute of Geology, Chinese Academy of Geological Sciences, is one of the most renowned paleontological fossil databases in China. This system not only provides rich fossil text information but also contains a large amount of fossil search image data, allowing users to search using both text and image formats. Furthermore, the system visualizes the fossil's geographic location, geological age, and paleogeographic location, providing users with a more intuitive and convenient query experience.

[0004] In addition to the aforementioned systems, many other types of paleontological fossil databases exist both domestically and internationally. These databases differ in their data organization methods and online functionality. For example, some databases are based on fossil specimens or fossil search images, primarily providing cataloging, querying, online browsing, and physical loan services for fossil specimens in collections. Other databases, on the other hand, are based on research subjects such as fossil occurrence records, localities, or geological profiles, primarily serving frontline researchers.

[0005] However, there are some problems in the process of searching through the database system that lead to inaccurate search results, so a more accurate database search method is needed.

[0006] The existing paleontological fossil database system obtains search results by searching text and images for related searches, and outputs the search results to realize the search function of the paleontological fossil database system.

[0007] For example, the patent application with publication number CN118193611A discloses a three-dimensional modeling database service platform for important geological drilling data, including: a data quality inspection module, which performs quality inspection on the drilling data submitted from each area, stores the data that passes the quality inspection in the drilling database, and parses the data that fails the quality inspection and stores it in the drilling database; a data management module, which classifies the data in the drilling database into levels for retrieval by users with different permissions, and also updates the data in the drilling database; a data modeling module, which performs three-dimensional modeling on the drilling data; a data service module, which publishes the drilling data in the form of three-dimensional models; a drilling data retrieval module, which provides users with retrieval and display functions for published data; a special product module, which provides users with retrieval and display functions for special products related to drilling; and a data statistics module, which displays drilling data statistical results under various statistical categories to users.

[0008] For example, the patent application with publication number CN114266243A discloses a patent information processing service system based on word frequency and its service method, which includes: a dedicated memory, an automatic storage module, an association matching module, a thematic data service module, a technology supply and demand matching module and a patent licensing evaluation auxiliary decision module. The dedicated memory is used to store alternative word databases, the automatic storage module is used to establish alternative word databases and obtain standardized retrieval procedures, and within a first interval time, the words in the alternative word database are used as keywords to search the patent database in all fields to obtain the first patent information.

[0009] However, in the process of implementing the technical solutions of the embodiments of the present application, the present application discovered that the above technology has at least the following technical problems:

[0010] In the prior art, during the retrieval process using the paleontological fossil standard database special service system based on input text and images, the quality of the input image and the level of detail of the text will affect the accuracy of the retrieval results, resulting in inaccurate retrieval results provided by the paleontological fossil standard database. Summary of the Invention

[0011] The embodiment of the present application solves the problem of inaccurate search results provided by the paleontological fossil standard database in the prior art by providing a paleontological fossil standard database special service system, thereby improving the search effectiveness of the paleontological fossil standard database.

[0012] An embodiment of the present application provides a paleontological fossil standard database special service system, including: an information input module, a feature extraction module, an image processing module and a retrieval output module; wherein, the information input module is used to input fossil retrieval images and retrieval texts into the paleontological fossil standard database; the feature extraction module is used to analyze the integrity of the fossil area based on the fossil retrieval image and determine whether to perform fossil retrieval image feature extraction; the image processing module is used to analyze whether to perform fossil retrieval image processing adjustment after performing fossil retrieval image feature extraction; the retrieval output module is used to retrieve retrieval information based on the obtained fossil retrieval image features and retrieval text after the fossil retrieval image processing adjustment, and analyze the retrieval information to determine whether to output the retrieval information.

[0013] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0014] 1. By inputting the fossil retrieval image and retrieval text into the paleontological fossil standard database, analyzing the integrity of the fossil area according to the fossil retrieval image and judging whether to perform fossil retrieval image feature extraction, analyzing whether to perform fossil retrieval image processing and adjustment after the fossil retrieval image feature extraction, searching according to the obtained fossil retrieval image features and retrieval text after the fossil retrieval image processing and adjustment to obtain retrieval information, analyzing the retrieval information to judge whether to output the retrieval information, thereby outputting the retrieval information with high content accuracy as the retrieval result, thereby achieving the improvement of the retrieval effectiveness of the paleontological fossil standard database, and effectively solving the problem of inaccurate retrieval results provided by the paleontological fossil standard database in the prior art.

[0015] 2. Obtain fossil area integrity data through fossil retrieval images, quantify the degree of area integrity based on the fossil area integrity data, and obtain a fossil area integrity assessment value. Then, determine whether to perform fossil retrieval image feature extraction based on the fossil area integrity, and then obtain more comprehensive fossil features after feature extraction based on fossil retrieval images that meet the integrity standards.

[0016] 3. After performing fossil retrieval image feature extraction, the fossil area feature extraction effect data is obtained, the fossil area feature extraction effect is quantified according to the fossil area feature extraction effect data, and the fossil area feature extraction effect evaluation value is obtained. According to the fossil area feature extraction effect evaluation value, it is determined whether to perform fossil retrieval image processing adjustment, and feature extraction is performed on the fossil retrieval image after the fossil retrieval image processing adjustment, thereby achieving fossil features with significantly improved feature extraction effect, more representativeness and discrimination.

[0017] 4. Obtain search result matching data based on the search information and search text, obtain the search result matching degree based on the search result matching data analysis, analyze the content matching degree of the search information based on the search result matching degree, and provide search output feedback based on the content matching degree of the search information, thereby obtaining more accurate search output results through the paleontological fossil standard database special service system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of the structure of a paleontological fossil standard database special service system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The embodiment of the present application solves the problem of inaccurate retrieval results provided by the paleontological fossil standard database in the prior art by providing a paleontological fossil standard database special service system. The system inputs a fossil retrieval image and a retrieval text into the paleontological fossil standard database, analyzes the integrity of the fossil area based on the fossil retrieval image and determines whether to perform fossil retrieval image feature extraction, analyzes whether to perform fossil retrieval image processing and adjustment after the fossil retrieval image feature extraction, retrieves the retrieval information based on the obtained fossil retrieval image features and retrieval text after the fossil retrieval image processing and adjustment, analyzes the retrieval information and determines whether to output the retrieval information, thereby outputting retrieval information with high content accuracy as the retrieval result, thereby improving the retrieval effectiveness of the paleontological fossil standard database.

[0020] The technical solution in the embodiment of the present application is to solve the problem of inaccurate search results provided by the above-mentioned paleontological fossil standard database. The overall idea is as follows:

[0021] By inputting fossil retrieval images and retrieval texts into a paleontological fossil standard database, fossil area integrity data is obtained through the fossil retrieval images, the degree of area integrity is quantified based on the fossil area integrity data, and a fossil area integrity evaluation value is obtained, thereby judging whether to perform fossil retrieval image feature extraction based on the fossil area integrity evaluation value, and obtaining fossil area feature extraction effect data after performing fossil retrieval image feature extraction, quantifying the fossil area feature extraction effect based on the fossil area feature extraction effect data, and obtaining a fossil area feature extraction effect evaluation value, and judging whether to perform fossil retrieval image processing adjustment based on the fossil area feature extraction effect evaluation value, after the fossil retrieval image processing adjustment, retrieval is performed based on the obtained fossil retrieval image features and retrieval text to obtain retrieval information, and retrieval result matching data is obtained based on the retrieval result matching data analysis to obtain a retrieval result matching degree, and the content matching degree of the retrieval information is analyzed based on the retrieval result matching degree, and retrieval output feedback is performed based on the content matching degree of the retrieval information, and retrieval information with high content accuracy is output as a retrieval result, thereby achieving the effect of improving the retrieval effectiveness of the paleontological fossil standard database.

[0022] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0023] like Figure 1 As shown, it is a structural diagram of a paleontological fossil standard database special service system provided by an embodiment of the present application. The paleontological fossil standard database special service system provided by an embodiment of the present application includes: an information input module, a feature extraction module, an image processing module and a retrieval output module; wherein, the information input module is used to input fossil retrieval images and retrieval texts into the paleontological fossil standard database; the feature extraction module is used to analyze the integrity of the fossil area according to the fossil retrieval image and determine whether to perform fossil retrieval image feature extraction; the image processing module is used to analyze whether to perform fossil retrieval image processing adjustment after performing fossil retrieval image feature extraction; the retrieval output module is used to retrieve retrieval information according to the obtained fossil retrieval image features and retrieval text after the fossil retrieval image processing adjustment, and analyze the retrieval information to determine whether to output the retrieval information.

[0024] Furthermore, the specific analysis process of analyzing the integrity of the fossil area based on the fossil retrieval image is as follows: fossil area integrity data is obtained based on the fossil retrieval image; the fossil area integrity data includes: fossil area intersection area, fossil area union area, fossil area, fossil contour fracture length, fossil contour fracture number and fossil contour curvature standard deviation; the degree of integrity of the area is quantified according to the fossil area integrity data to obtain a fossil area integrity evaluation value, and the fossil area integrity evaluation value is used to quantitatively analyze the integrity of the fossil area in the fossil retrieval image; the fossil area integrity evaluation value is compared with a preset fossil area integrity threshold obtained from the database, when the fossil area integrity evaluation value is less than the preset fossil area integrity threshold obtained from the database, it indicates that the fossil area integrity is unqualified; when in other situations, it indicates that the fossil area integrity is qualified; the specific analysis process of judging whether to perform feature extraction of the fossil retrieval image is as follows: when the fossil area integrity is qualified, feature extraction is performed on the fossil retrieval image; when the fossil area integrity is unqualified, feature extraction is not performed on the fossil retrieval image, and the user is prompted to re-enter the fossil retrieval image; when the fossil area integrity of the monitored fossil retrieval image is qualified, feature extraction is performed on the fossil retrieval image.

[0025] In this embodiment, the fossil area and the background area in the fossil retrieval image are separated by an image segmentation algorithm (such as threshold segmentation, region growing, edge detection, etc.) to obtain the fossil area, and the image registration technology is improved to align the standardized fossil template with the fossil area obtained by segmentation to ensure that the standardized fossil template and the fossil area are consistent in position and angle. After alignment, the intersection area between the fossil area and the standardized fossil template is calculated. This area reflects the common part between the two, that is, the fossil area intersection area, unit: square pixel. Similarly, the union area of ​​the fossil area and the standardized complete fossil template is obtained, that is, the total area covered by the two, that is, the fossil area union area, unit: square pixel. The ratio of the intersection area to the union area represents the overlap, and the overlap value is between 0 and 1, wherein: the overlap is 1: it means that the fossil area obtained by segmentation completely overlaps with the standardized template, without any missing or occlusion; the closer the overlap is to 0, the smaller the overlap between the fossil area and the standardized template, and the greater the possible missing or occlusion.

[0026] The area of ​​the fossil region obtained through image segmentation is the fossil area, measured in square pixels. The expected area estimated from the database based on a standardized complete fossil template is the minimum complete fossil area, measured in square pixels. The ratio of the fossil area to the minimum complete fossil area indicates the completeness of the fossil. A smaller ratio indicates a less complete fossil, potentially indicating missing or fragmented parts.

[0027] Use an edge detection algorithm (such as Canny edge detection) to process the fossil retrieval image and extract the fossil's contour line. The edge detection algorithm can identify brightness changes in the image and mark these changes as edges, thereby obtaining the fossil's contour line. On the extracted contour line, identify the broken or discontinuous parts. This can be achieved by observing the continuity of the contour line. If there are gaps or jumps in the contour line, it indicates that there is a break. For each identified broken part, calculate its length. The break length can be obtained by calculating the distance between the two end points of the broken part. If the broken part is composed of multiple line segments, it is necessary to calculate the length of each line segment separately and sum them to obtain the fossil contour break length, unit: pixel. Count the total number of broken parts on the contour line to obtain the number of fossil contour breaks, which has no unit (or is expressed as "pieces"). The number of breaks directly reflects the degree of continuity of the contour line. The more breaks there are, the worse the continuity of the contour line.

[0028] Get the preset maximum fracture length of fossil outlines from the database, in pixels, and the maximum fracture number of fossil outlines, without units (or expressed as "pieces").

[0029] Use an edge detection algorithm (such as Canny edge detection) to extract the outline of the fossil. A series of discrete contour points are extracted from the outline. For each contour point, its curvature is calculated. The curvature describes the degree of curvature of the contour line at that point. Curvature can be calculated by a variety of methods, such as using a curvature estimation algorithm for a discrete point set, or by fitting a local curve (such as a circle or a parabola) to estimate the curvature. Calculate the average of the curvature values ​​of all contour points, calculate the square of the difference between each curvature value and the average, and find the average of these squared differences (i.e., the variance). Take the square root of the variance to obtain the standard deviation, which is the standard deviation of the fossil contour curvature, and has no unit. The curvature standard deviation reflects the degree of discreteness of the curvature change on the contour line. The larger the standard deviation, the more drastic the curvature change and the worse the consistency, indicating that the curvature of the contour line changes drastically, and may be broken, deformed, or affected by other factors.

[0030] Get the preset maximum curvature standard deviation of the fossil outline from the database, without unit.

[0031] By analyzing the integrity of the fossil area from the aspects of the intersection area of ​​fossil areas, the union area of ​​fossil areas, the area of ​​fossil areas, the minimum complete fossil area, the length of fossil outline breaks, the maximum length of fossil outline breaks, the number of fossil outline breaks, the maximum number of fossil outline breaks, the standard deviation of fossil outline curvature, and the standard deviation of the maximum curvature of fossil outline, the analysis of the integrity of the fossil area is more comprehensive, which is conducive to more accurately clarifying the integrity of the fossil area.

[0032] When the fossil area integrity assessment value is less than the preset fossil area integrity threshold obtained from the database, it indicates that the fossil area integrity is unqualified, and feature extraction is not performed on the fossil retrieval image. The user is prompted to re-enter the fossil retrieval image. When the fossil area integrity of the monitored fossil retrieval image is qualified, feature extraction is performed on the fossil retrieval image; when in other situations, it indicates that the fossil area integrity is qualified, and feature extraction is performed on the fossil retrieval image.

[0033] Furthermore, the degree of regional integrity is quantified according to the fossil area integrity data, and the specific process for obtaining the fossil area integrity assessment value is as follows: the intersection area of ​​the fossil area is compared with the union area of ​​the fossil area, and the overlap index is obtained by weighting the intersection area weight factor; the fossil area is compared with the minimum complete fossil area, and the area index is obtained by weighting the area weight factor; the fossil contour fracture length is compared with the maximum fossil contour fracture length, and the fracture length score is obtained by weighting the fracture length weight factor; the number of fossil contour fractures is compared with the maximum number of fossil contour fractures, and the fracture number score is obtained by weighting the fracture number weight factor; the fracture length score is coupled with the fracture number score and then an inverse proportional operation is performed, and the contour fracture degree index is obtained by weighting the contour fracture degree weight factor; the maximum curvature standard deviation of the fossil contour is compared with the standard deviation of the fossil contour curvature, and the curvature index is obtained by weighting the contour curvature weight factor; the overlap index, area index, contour fracture degree index and curvature index are coupled to obtain the fossil area integrity assessment value.

[0034] In this embodiment, the specific method for obtaining the fossil area integrity assessment value is:

[0035]

[0036] where ρ is the fossil area integrity assessment value of the fossil area, QQR is the fossil area intersection area between the fossil area and the standardized complete fossil template, QQT is the fossil area union area between the fossil area and the standardized complete fossil template, QQW is the fossil area, QW is the minimum complete fossil area, QQU is the fossil outline break length, QU is the maximum fossil outline break length, QQL is the number of fossil outline breaks, QL is the maximum number of fossil outline breaks, QQJ is the standard deviation of fossil outline curvature, QJ is the standard deviation of the maximum fossil outline curvature, ρ1 is the intersection area weight factor, ρ2 is the area weight factor, ρ3 is the outline break degree weight factor, ρ4 is the outline curvature weight factor, Q1 is the break length weight factor, and Q2 is the break number weight factor.

[0037] The smaller the ratio of the intersection area of ​​the fossil area to the union area of ​​the fossil area, the greater the probability that the fossil retrieval image is damaged or incomplete, the smaller the fossil area may be, and the smaller the ratio of the fossil area to the minimum complete fossil area, the more serious the damage to the fossil area of ​​the fossil retrieval image. Therefore, the longer the fossil contour break length and the greater the ratio to the maximum fossil contour break length, the greater the number of fossil contour breaks and the greater the ratio to the maximum number of fossil contour breaks, the larger the corresponding fossil contour curvature standard deviation, and the smaller the ratio of the maximum fossil contour curvature standard deviation to the fossil contour curvature standard deviation. Therefore, the smaller the fossil area integrity assessment value, the less complete the fossil area of ​​the fossil retrieval image.

[0038] The intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor are obtained from the database. The intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor respectively represent the degree of influence of the overlap index, area index, contour fracture degree index, and curvature index on the fossil area integrity assessment value. There is a one-to-one mapping relationship between the overlap index, area index, contour fracture degree index, and curvature index and the corresponding intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor, and the sum of the intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor is equal to one. For example, the real-time overlap index, area index, contour fracture degree index, and curvature index are input into the corresponding mapping relationship to obtain the corresponding intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor.

[0039] A fracture length weighting factor and a fracture number weighting factor are obtained from the database. The fracture length weighting factor and the fracture number weighting factor respectively represent the degree of influence of the fossil outline fracture length and the fossil outline fracture number on the fossil area integrity assessment value. A one-to-one mapping relationship exists between the fossil outline fracture length and the fossil outline fracture number and the corresponding fracture length weighting factor and fracture number weighting factor, respectively, and the sum of the fracture length weighting factor and the fracture number weighting factor is equal to one. For example, the real-time fossil outline fracture length and the fossil outline fracture number are input into the corresponding mapping relationship to obtain the corresponding fracture length weighting factor and fracture number weighting factor.

[0040] Furthermore, the specific analysis process of analyzing whether to perform fossil retrieval image processing adjustment after performing fossil retrieval image feature extraction is as follows: after performing fossil retrieval image feature extraction, fossil area feature extraction effect data is obtained; the fossil area feature extraction effect data includes: fossil area Laplacian variance, fossil area noise level, fossil area high-frequency component ratio and fossil area contrast; the fossil area feature extraction effect is quantified according to the fossil area feature extraction effect data to obtain a fossil area feature extraction effect evaluation value, and the fossil area feature extraction effect evaluation value is used to quantitatively analyze the effect of feature extraction of the fossil area of ​​the fossil retrieval image; and whether to perform fossil retrieval image processing adjustment is determined according to the fossil area feature extraction effect evaluation value.

[0041] In this embodiment, the low-frequency component in the blurred image accounts for too high a proportion, resulting in loss of detailed shape information. Fourier descriptor feature descriptors may not accurately reflect the shape characteristics of the fossil in the blurred image. In fossil retrieval image analysis, this detailed shape information is crucial for identifying the type and age of the fossil. However, blurred images may cause the values ​​of these feature descriptors to deviate from their true values, thus affecting subsequent classification and recognition results.

[0042] Noise interference can cause anomalies in GLCM (Gray-level Co-occurrence Matrix) texture metrics (such as contrast and entropy). The lower the signal-to-noise ratio (SNR), the greater the error in these metrics. In fossil retrieval images, noise can mask or distort the texture information of the fossil, making the GLCM texture metrics inaccurate in reflecting the fossil's textural characteristics. This can affect analysis of the fossil's surface structure and sedimentary environment.

[0043] As a quantitative indicator of clarity, the higher the Laplacian variance, the clearer the image. In fossil retrieval image feature extraction, a higher Laplacian variance generally means more accurate contour parameters and richer shape information.

[0044] As quantitative indicators of noise levels, higher signal-to-noise ratios and lower noise variances indicate better image quality. In fossil retrieval image feature extraction, higher signal-to-noise ratios and lower noise variances generally indicate more accurate texture metrics and more reliable microstructural information.

[0045] Therefore, analyzing the feature extraction effect of the fossil retrieval image from the Laplacian variance of the fossil area, the preset Laplacian variance of the fossil area, the noise level of the fossil area, the preset noise level of the fossil area, the proportion of high-frequency components in the fossil area, the proportion of preset high-frequency components in the fossil area, the contrast of the fossil area, the preset contrast of the fossil area, the entropy value of the fossil area, and the preset entropy value of the fossil area of ​​the fossil retrieval image can more accurately clarify the feature extraction effect.

[0046] Furthermore, the specific process of determining whether to perform fossil retrieval image processing adjustment based on the fossil area feature extraction effect evaluation value is as follows: obtaining a preset feature extraction effect threshold from the database; when the fossil area feature extraction effect evaluation value is less than the preset feature extraction effect threshold obtained from the database, performing fossil retrieval image processing adjustment; when in other situations, not performing fossil retrieval image processing adjustment.

[0047] In this embodiment, when the evaluation value of the fossil area feature extraction effect is less than the preset feature extraction effect threshold obtained from the database, it means that the fossil area feature extraction effect is unqualified, and the fossil retrieval image processing adjustment is performed; when in other situations, it means that the fossil area feature extraction effect is qualified, and the fossil retrieval image processing adjustment is not performed.

[0048] Furthermore, the fossil retrieval image processing adjustment includes Laplace sharpening adjustment, high-pass filtering adjustment and early warning prompts; the specific process of Laplace sharpening adjustment is: mapping with the fossil area feature extraction effect evaluation value to obtain the corresponding Laplace kernel value, convolving the fossil retrieval image with the Laplace operator of the Laplace kernel value to obtain the sharpened fossil retrieval image, analyzing whether the fossil area feature extraction effect evaluation value of the fossil retrieval image is not less than the preset feature extraction effect threshold obtained from the database, when the fossil area feature extraction effect evaluation value of the fossil retrieval image is less than the preset feature extraction effect threshold obtained from the database, repeating the above adjustment, when the growth range of the Laplacian variance is less than the preset Laplacian variance growth range or the fossil area feature extraction effect evaluation value is not less than the preset feature extraction effect threshold obtained from the database, stopping the Laplace sharpening adjustment; the specific process of high-pass filtering adjustment is: when the Laplace sharpening adjustment is stopped, the fossil area feature extraction effect evaluation value is less than the preset feature extraction effect threshold obtained from the database. The preset feature extraction effect threshold obtained from the database is obtained, and the corresponding filtering strength is obtained according to the fossil area feature extraction effect evaluation value, and the fossil retrieval image is high-pass filtered with the filtering strength, and the fossil area feature extraction effect evaluation value of the fossil retrieval image after high-pass filtering is analyzed to see whether it is not less than the preset feature extraction effect threshold obtained from the database. When the fossil area feature extraction effect evaluation value of the fossil retrieval image is less than the preset feature extraction effect threshold obtained from the database, the above adjustment is repeated. When the high-frequency component proportion of the fossil retrieval image is greater than the preset high-frequency component proportion or the fossil area feature extraction effect evaluation value is not less than the preset feature extraction effect threshold obtained from the database, the high-pass filtering adjustment is stopped. The specific process of the early warning prompt is: when the high-pass filtering adjustment is stopped, if the fossil area feature extraction effect evaluation value is less than the preset feature extraction effect threshold obtained from the database, it means that the feature extraction effect of the fossil retrieval image after Laplace sharpening adjustment and high-pass filtering adjustment is unqualified, and the user is prompted to change the fossil retrieval image.

[0049] In this embodiment, the Laplacian sharpening algorithm is used to enhance the edge and detail information in the image and improve the clarity of the image. The sharpening filter can emphasize the difference between edge pixels, making the details more distinct.

[0050] Using a high-pass filter allows high-frequency components to pass through while blocking low-frequency components. This can enhance the details and texture information in the image and increase the proportion of high-frequency components.

[0051] Monitor the changes in Laplacian variance to evaluate the improvement in image clarity. When the Laplacian variance increases to a certain level and no longer increases significantly, it can be considered that the image clarity has been sufficiently improved.

[0052] The proportion of high-frequency components in the image is calculated through methods such as Fourier transform to evaluate the retention of image detail information. When the proportion of high-frequency components increases to a certain level and the image details become richer, it can be considered that the high-frequency components are appropriately retained.

[0053] When the effect of feature extraction after Laplace sharpening adjustment and high-pass filtering is unsatisfactory, it means that the input fossil retrieval image is too blurry, and the user is prompted to re-input a clearer fossil retrieval image.

[0054] The corresponding Laplace kernel value and filter strength are obtained from the database based on the fossil region feature extraction effect evaluation value. There is a one-to-one or many-to-one mapping relationship between the fossil region feature extraction effect evaluation value, the Laplace kernel value, and the filter strength. For example, the corresponding Laplace kernel value and filter strength are obtained based on the mapping relationship between the real-time fossil region feature extraction effect evaluation value, the Laplace kernel value, and the filter strength.

[0055] Furthermore, the fossil area feature extraction effect is quantified according to the fossil area feature extraction effect data, and the specific process of obtaining the fossil area feature extraction effect evaluation value is as follows: the Laplacian variance of the fossil area is measured with the preset Laplacian variance of the fossil area, and the variance index is obtained by weighting the variance deviation measurement result by the variance weight factor; the noise level of the fossil area is coupled with the preset noise level of the fossil area and then compared with the preset noise level of the fossil area, and the noise level index is obtained by weighting the comparison result by the noise level weight factor; the proportion of high-frequency components in the fossil area is compared with the preset high-frequency components in the fossil area. After measuring the high-frequency component deviation of the proportion, it is compared with the preset high-frequency component proportion of the fossil area, and the high-frequency component proportion index is obtained by weighting the high-frequency component weight factor; the fossil area contrast is compared with the preset contrast of the fossil area, and the contrast index is obtained by weighting the contrast weight factor; the preset entropy value of the fossil area is compared with the entropy value of the fossil area, and the entropy index is obtained by weighting the entropy weight factor; the variance index, noise level index, high-frequency component proportion index, contrast index and entropy index are coupled to obtain the evaluation value of the fossil area feature extraction effect.

[0056] In this embodiment, the Laplacian variance of the fossil region is obtained by performing a convolution operation on the image of the fossil region using the Laplacian operator, calculating the Laplacian value of each pixel, and taking the variance of the Laplacian values ​​of all pixels to obtain the unitless Laplacian variance of the fossil region. For implementation, the Laplacian function and variance calculation function in an image processing library (such as OpenCV) can be used.

[0057] Method for obtaining the noise level in the fossil area: The noise level can be assessed by calculating the signal-to-noise ratio (SNR) of the image. The SNR is calculated by dividing the image signal power by the noise power. The unit of the SNR is usually decibel (dB).

[0058] To determine the proportion of high-frequency components in the fossil area, use Fourier transform to convert the fossil area image to the frequency domain. Calculate the energy or amplitude of the high-frequency components in the frequency domain and compare them with the total energy or amplitude to obtain the unitless proportion of high-frequency components. This can be achieved using the Fourier transform and energy calculation functions in the image processing library.

[0059] Method for obtaining the contrast of the fossil area: Calculate the standard deviation of the grayscale histogram in the fossil area image, without unit.

[0060] Method for obtaining the entropy value of the fossil area: The entropy value of the grayscale histogram of the fossil area image is calculated according to the calculation formula of information entropy. The unit is bit, which reflects the complexity and information content of the grayscale distribution in the image.

[0061] Get the preset Laplacian variance of the fossil area from the database, unitless, the preset noise level of the fossil area, unit: signal-to-noise ratio (SNR) is usually in decibels (dB), the preset high-frequency component ratio of the fossil area, unitless, the preset contrast of the fossil area, unitless, and the preset entropy value of the fossil area, unit: bit.

[0062] The specific method for obtaining the evaluation value of the fossil area feature extraction effect is as follows:

[0063]

[0064] Where, It is expressed as the evaluation value of the feature extraction effect of the fossil area, LLO is expressed as the Laplacian variance of the fossil area, LO is expressed as the preset Laplacian variance of the fossil area, LLZ is expressed as the noise level of the fossil area, LZ is expressed as the preset noise level of the fossil area, LLR is expressed as the proportion of high-frequency components in the fossil area, LR is expressed as the proportion of preset high-frequency components in the fossil area, LLK is expressed as the contrast of the fossil area, LK is expressed as the preset contrast of the fossil area, LLU is expressed as the entropy value of the fossil area, LU is expressed as the preset entropy value of the fossil area, Expressed as the variance weight factor, Expressed as the noise level weight factor, Expressed as the high-frequency component weight factor, Expressed as a contrast weighting factor, Expressed as entropy weight factor.

[0065] The variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor and entropy weight factor are obtained from the database. The variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor and entropy weight factor respectively represent the influence of the Laplacian variance of the fossil area, the noise level of the fossil area, the proportion of high-frequency components in the fossil area, the contrast of the fossil area and the entropy value of the fossil area on the evaluation value of the feature extraction effect of the fossil area. There is a one-to-one mapping relationship between the Laplacian variance of the fossil area, the noise level of the fossil area, the proportion of high-frequency components in the fossil area, the contrast of the fossil area and the entropy value of the fossil area and the corresponding variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor and entropy weight factor, and the sum of the variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor and entropy weight factor is equal to one. For example, the real-time Laplacian variance of the fossil area, the noise level of the fossil area, the proportion of high-frequency components in the fossil area, the contrast of the fossil area, and the entropy value of the fossil area are input into the corresponding mapping relationship to obtain the corresponding variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor, and entropy value weight factor.

[0066] Furthermore, the specific analysis process of analyzing the retrieval information to determine whether to output the retrieval information is as follows: obtaining retrieval result matching data based on the retrieval information and the retrieval text, obtaining the retrieval result matching degree based on the analysis of the retrieval result matching data, and the retrieval result matching degree is used to quantitatively analyze the content matching degree between the retrieval information and the retrieval text; analyzing the content matching degree of the retrieval information based on the retrieval result matching degree; the specific analysis process of analyzing the content matching degree of the retrieval information based on the retrieval result matching degree is as follows: obtaining a preset retrieval result matching first threshold and a retrieval result matching second threshold from the database, when the retrieval result matching degree is less than the preset retrieval result matching first threshold obtained from the database, it indicates that the retrieval information is completely matched; when the retrieval result matching degree is not less than the preset retrieval result matching first threshold obtained from the database and not greater than the retrieval result matching second threshold, it indicates that the retrieval information is not completely matched; when the retrieval result matching degree is greater than the preset retrieval result matching first threshold obtained from the database, it indicates that the retrieval information is not matched; and retrieval output feedback is performed based on the content matching degree of the retrieval information.

[0067] In this embodiment, when the retrieval result matching degree is smaller, it indicates that the content matching degree of the retrieval information is lower; when the retrieval result matching degree is larger, it indicates that the content matching degree of the retrieval information is higher.

[0068] Furthermore, the specific analysis process for retrieval output feedback based on the degree of content matching of the retrieval information is as follows: when the retrieval information is completely matched, the corresponding retrieval information is output as the retrieval result; when the retrieval information is not completely matched, a prompt is given that the retrieval information is not completely matched, and a selection operation is sent to the user whether to output the retrieval information as the retrieval result. When the user selects yes, the retrieval information is output as the retrieval result; otherwise, the user is prompted to supplement the retrieval text until the corresponding retrieval information is output as the retrieval result; when the retrieval information is not matched, the user is prompted to supplement the retrieval text until the corresponding retrieval information is output as the retrieval result.

[0069] In this embodiment, when the search information is completely matched, the probability that the search information is the content expected by the user is high, and the corresponding search information is output as the search result; when the search information is not completely matched, the probability that the search information is the content expected by the user is medium, a prompt is given that the search information is not completely matched, and a selection operation is sent to the user whether to output the search information as the search result. When the user selects yes, the search information is output as the search result, otherwise, the user is prompted to supplement the search text until the corresponding search information is output as the search result; when the search information is not matched, the probability that the search information is the content expected by the user is low, and the user is prompted to supplement the search text until the corresponding search information is output as the search result

[0070] Furthermore, the retrieval result matching data includes: retrieval topic matching score, core content coverage, detail information consistency rate and semantic similarity score; the specific analysis process of retrieval result matching obtained based on the analysis of retrieval result matching data is: weighting the retrieval topic matching score and the retrieval topic matching score weight factor to obtain the retrieval topic index; weighting the core content coverage and the core content coverage weight factor to obtain the core content index; weighting the detail information consistency rate and the detail information consistency rate weight factor to obtain the information detail index; weighting the semantic similarity score and the semantic similarity score weight factor to obtain the semantic similarity index; combining the retrieval topic index, core content index, information detail index and semantic similarity index for coupling processing to obtain the retrieval result matching degree.

[0071] In this embodiment, a text classification algorithm (such as TF-IDF combined with a naive Bayes classifier) ​​is used to classify the search text and the text corresponding to the search information to determine whether the two belong to the same topic category, and obtain a topic matching score (between 0 and 1, 1 indicates a perfect match), which has no unit.

[0072] The computer extracts key information points (such as species name, geological age, morphological characteristics, etc.) from the search text, and checks whether the text corresponding to the search information contains these information points, and obtains the core content coverage (number of covered information points / total number of information points), which is unitless.

[0073] The computer compares the specific detail information (such as size, color, storage status, etc.) in the search text and the text corresponding to the search information one by one to obtain the detail information consistency rate (number of consistent detail information / total number of detail information), which has no unit.

[0074] Use a word vector model (such as Word2Vec, GloVe, etc.) to convert the search text and the text corresponding to the search information into vector representations, calculate the cosine similarity between the two vectors as the semantic similarity score, and obtain the semantic similarity score (between 0 and 1, 1 indicates complete similarity), which has no unit.

[0075] The specific method for obtaining the matching degree of the search results is as follows:

[0076] γ=KKX*γ1+KKF*γ2+KKS*γ3+KKA*γ4;

[0077] Where γ represents the retrieval result matching degree, KKX represents the retrieval topic matching degree score, KKF represents the core content coverage, KKS represents the detail information consistency rate, KKA represents the semantic similarity score, γ1 represents the retrieval topic matching degree score weight factor, γ2 represents the core content coverage weight factor, γ3 represents the detail information consistency rate weight factor, and γ4 represents the semantic similarity score weight factor.

[0078] The retrieval topic matching score weight factor, core content coverage weight factor, detail information consistency rate weight factor and semantic similarity score weight factor are obtained from the database. The retrieval topic matching score weight factor, core content coverage weight factor, detail information consistency rate weight factor and semantic similarity score weight factor respectively represent the influence of the retrieval topic matching score, core content coverage, detail information consistency rate and semantic similarity score on the evaluation value of the fossil area feature extraction effect. There is a one-to-one mapping relationship between the retrieval topic matching score weight factor, core content coverage weight factor, detail information consistency rate weight factor and semantic similarity score weight factor and the corresponding retrieval topic matching score weight factor, core content coverage weight factor, detail information consistency rate weight factor and semantic similarity score weight factor, and the sum of the retrieval topic matching score weight factor, core content coverage weight factor, detail information consistency rate weight factor and semantic similarity score weight factor is equal to one. For example, the real-time retrieval topic matching score, core content coverage, detail information consistency rate, and semantic similarity score are input into the corresponding mapping relationship to obtain the corresponding retrieval topic matching score weight factor, core content coverage weight factor, detail information consistency rate weight factor, and semantic similarity score weight factor.

[0079] By analyzing the content matching between the retrieval information and the retrieval text from four aspects: retrieval topic matching score, core content coverage, detail information consistency rate, and semantic similarity score, the accuracy of the analysis of the content matching between the retrieval information and the retrieval text is increased, which is conducive to outputting more accurate retrieval results.

[0080] The technical solution in the above-mentioned embodiment of the present application is to input the fossil retrieval image and the retrieval text into the paleontological fossil standard database, analyze the integrity of the fossil area according to the fossil retrieval image and determine whether to perform fossil retrieval image feature extraction, analyze whether to perform fossil retrieval image processing and adjustment after the fossil retrieval image feature extraction, retrieve the retrieval information according to the obtained fossil retrieval image features and retrieval text after the fossil retrieval image processing and adjustment, analyze the retrieval information to determine whether to output the retrieval information, and output the retrieval information with high content accuracy as the retrieval result, thereby achieving the improvement of the retrieval effectiveness of the paleontological fossil standard database, and effectively solving the problem of inaccurate retrieval results provided by the paleontological fossil standard database in the prior art.

[0081] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0082] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0083] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0084] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0085] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0086] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A paleontological fossil standard database special service system, characterized by: include: Information input module, feature extraction module, image processing module and retrieval output module; Wherein, the information input module is used to input the fossil search image and search text into the paleontological fossil standard database; The feature extraction module is used to analyze the integrity of the fossil area based on the fossil retrieval image and determine whether to perform fossil retrieval image feature extraction; The image processing module is used to extract features from fossil retrieval images and then analyze whether to perform fossil retrieval image processing and adjustment; The retrieval output module is used to retrieve the retrieval information based on the obtained fossil retrieval image features and retrieval text after the fossil retrieval image is processed and adjusted, and analyze the retrieval information to determine whether to output the retrieval information; The specific analysis process of analyzing the integrity of the fossil area based on the fossil retrieval image is as follows: Obtain fossil area integrity data based on fossil retrieval images; The fossil area integrity data include: fossil area intersection area, fossil area union area, fossil area area, fossil outline break length, fossil outline break number and fossil outline curvature standard deviation; quantifying the integrity of the region according to the fossil region integrity data to obtain a fossil region integrity assessment value, wherein the fossil region integrity assessment value is used to quantitatively analyze the integrity of the fossil region in the fossil retrieval image; Comparing the fossil area integrity assessment value with a preset fossil area integrity threshold obtained from a database, when the fossil area integrity assessment value is less than the preset fossil area integrity threshold obtained from the database, it indicates that the fossil area integrity is unqualified; In other cases, it indicates that the integrity of the fossil area is qualified; The specific analysis process for determining whether to perform fossil retrieval image feature extraction is as follows: When the integrity of the fossil area is qualified, feature extraction is performed on the fossil retrieval image; When the integrity of the fossil region is unqualified, feature extraction is not performed on the fossil retrieval image, and the user is prompted to re-enter the fossil retrieval image. When the integrity of the fossil region of the monitored fossil retrieval image is qualified, feature extraction is performed on the fossil retrieval image. The specific process of quantifying the integrity of the region based on the fossil region integrity data and obtaining the fossil region integrity assessment value is as follows: The intersection area of ​​the fossil areas is compared with the union area of ​​the fossil areas, and the overlap index is obtained by weighting the comparison results with the intersection area weight factor. The area of ​​the fossil region is compared with the minimum complete fossil area, and the area index is obtained by weighting the comparison results with the area weight factor. The fracture length of the fossil outline is compared with the maximum fracture length of the fossil outline, and the fracture length score is obtained by weighting the comparison results with the fracture length weight factor. After comparing the number of fractures in the fossil outline with the maximum number of fractures in the fossil outline, the fracture number score is obtained by weighting the result of the comparison operation using the fracture number weight factor. The fracture length fraction and the fracture number fraction are coupled and then subjected to inverse proportional operation. The result of the inverse proportional operation is weighted by the contour fracture degree weight factor to obtain the contour fracture degree index. The maximum curvature standard deviation of the fossil outline is compared with the standard deviation of the fossil outline curvature, and the curvature index is obtained by weighting the contrast calculation results with the outline curvature weight factor. The overlap index, area index, contour fracture index and curvature index are coupled and processed to obtain the fossil area integrity assessment value.

2. A paleontological fossil standard database special service system as claimed in claim 1, characterized in that: The specific analysis process of analyzing whether to perform fossil retrieval image processing adjustment after performing fossil retrieval image feature extraction is as follows: After performing fossil retrieval image feature extraction, the fossil area feature extraction effect data is obtained; The fossil area feature extraction effect data includes: fossil area Laplacian variance, fossil area noise level, fossil area high frequency component ratio and fossil area contrast; quantifying the fossil region feature extraction effect according to the fossil region feature extraction effect data to obtain a fossil region feature extraction effect evaluation value, wherein the fossil region feature extraction effect evaluation value is used to quantitatively analyze the effect of feature extraction of the fossil region of the fossil retrieval image; Whether to perform fossil retrieval image processing adjustment is determined based on the evaluation value of the fossil area feature extraction effect.

3. A paleontological fossil standard database special service system as claimed in claim 2, characterized in that: The specific process of judging whether to perform fossil retrieval image processing adjustment according to the fossil area feature extraction effect evaluation value is as follows: Obtaining a preset feature extraction effect threshold from a database, and performing fossil retrieval image processing adjustment when the feature extraction effect evaluation value of the fossil area is less than the preset feature extraction effect threshold obtained from the database; In other cases, no fossil retrieval image processing adjustments are performed.

4. A paleontological fossil standard database special service system as claimed in claim 2, characterized in that: The fossil retrieval image processing adjustment includes Laplace sharpening adjustment, high-pass filtering adjustment and early warning prompts; The specific process of the Laplace sharpening adjustment is: Mapping the Laplace kernel value corresponding to the fossil region feature extraction effect evaluation value to obtain a corresponding Laplace kernel value, convolving the fossil retrieval image with the Laplace operator of the Laplace kernel value to obtain a sharpened fossil retrieval image, analyzing whether the fossil region feature extraction effect evaluation value of the fossil retrieval image is not less than a preset feature extraction effect threshold obtained from a database, repeating the above adjustment when the fossil region feature extraction effect evaluation value of the fossil retrieval image is less than the preset feature extraction effect threshold obtained from the database, and stopping the Laplace sharpening adjustment when the growth range of the Laplacian variance is less than the preset Laplacian variance growth range or the fossil region feature extraction effect evaluation value is not less than the preset feature extraction effect threshold obtained from the database; The specific process of the high-pass filter adjustment is as follows: When the Laplace sharpening adjustment is stopped and the fossil area feature extraction effect evaluation value is less than the preset feature extraction effect threshold obtained from the database, the corresponding filtering strength is obtained according to the fossil area feature extraction effect evaluation value, and the fossil retrieval image is high-pass filtered with the filtering strength. When the fossil area feature extraction effect evaluation value of the fossil retrieval image after high-pass filtering is less than the preset feature extraction effect threshold obtained from the database, the above adjustment is repeated. When the high-frequency component proportion of the fossil retrieval image is greater than the preset high-frequency component proportion or the fossil area feature extraction effect evaluation value is not less than the preset feature extraction effect threshold obtained from the database, the high-pass filtering adjustment is stopped.

5. A paleontological fossil standard database special service system as claimed in claim 2, characterized in that: The specific process of quantifying the fossil area feature extraction effect according to the fossil area feature extraction effect data and obtaining the fossil area feature extraction effect evaluation value is as follows: The Laplacian variance of the fossil area is compared with the preset Laplacian variance of the fossil area to measure the variance deviation, and the variance index is obtained by weighting the variance deviation measurement results with the variance weight factor. The noise level in the fossil area is coupled with the preset noise level in the fossil area, and then compared with the preset noise level in the fossil area. The noise level index is obtained by weighting the comparison results with the noise level weight factor. The high-frequency component ratio of the fossil area is measured by the high-frequency component deviation from the preset high-frequency component ratio of the fossil area, and then compared with the preset high-frequency component ratio of the fossil area. The high-frequency component ratio index is obtained by weighting the comparison results with the high-frequency component weight factor; The contrast of the fossil area is compared with the preset contrast of the fossil area, and the contrast index is obtained by weighting the contrast weight factor. Compare the preset entropy value of the fossil area with the entropy value of the fossil area, and obtain the entropy index by weighting the comparison result with the entropy weight factor; The variance index, noise level index, high-frequency component ratio index, contrast index and entropy index were coupled and processed to obtain the evaluation value of the fossil area feature extraction effect.

6. A paleontological fossil standard database special service system as claimed in claim 1, characterized in that: The specific analysis process of analyzing the search information and determining whether to output the search information is as follows: Get the search result matching data based on the search information and search text, The retrieval result matching degree is obtained based on the retrieval result matching data analysis, and the retrieval result matching degree is used to quantitatively analyze the degree of content matching between the retrieval information and the retrieval text; Analyze the content matching degree of the retrieved information based on the matching degree of the retrieval results; The specific analysis process of analyzing the content matching degree of the search information according to the search result matching degree is as follows: Obtaining a preset search result matching first threshold and a search result matching second threshold from the database, when the search result matching degree is less than the preset search result matching first threshold obtained from the database, it indicates that the search information is completely matched; When the retrieval result matching degree is not less than the preset retrieval result matching first threshold value obtained from the database and is not greater than the retrieval result matching second threshold value, it indicates that the retrieval information is not completely matched; When the search result matching degree is greater than a preset search result matching first threshold obtained from the database, it indicates that the search information does not match; The search output feedback is provided based on the content matching degree of the search information.

7. A paleontological fossil standard database special service system as claimed in claim 6, characterized in that: The specific analysis process of performing search output feedback based on the content matching degree of the search information is as follows: When the search information is completely matched, the corresponding search information is output as the search result; When the search information does not completely match, a selection operation is sent to the user as to whether to output the search information as the search result. If the user selects yes, the search information is output as the search result. Otherwise, the user is prompted to supplement the search text. When the search information does not match, the user is prompted to supplement the search text until the corresponding search information is output as the search result.

8. A paleontological fossil standard database special service system as claimed in claim 6, characterized in that: The search result matching data includes: search topic matching score, core content coverage, detail information consistency rate and semantic similarity score; The specific analysis process of obtaining the retrieval result matching degree based on the retrieval result matching data analysis is as follows: The search topic matching score and the search topic matching score weight factor are weighted to obtain the search topic index; The core content coverage and the core content coverage weight factor are weighted to obtain the core content index; The detail information consistency rate and the detail information consistency rate weight factor are weighted to obtain the information detail index; The semantic similarity score and the semantic similarity score weight factor are weighted to obtain the semantic similarity index; The retrieval result matching degree is obtained by coupling the retrieval topic index, core content index, information detail index and semantic similarity index.

Images