Data processing method, life circle display method and device, medium, and equipment

Abstract

A data processing method, a display method and device of a life circle, a medium and an equipment. The data processing method comprises: acquiring road data of a first urban area, POI data of each cell and life state data of each cell; based on the acquired road data and the POI data of each cell, dividing each cell into a life circle, and determining geographical position information of each cell in the first urban area; based on the geographical position information of each cell in the life circle and the life state data of each cell, using a preset clustering analysis algorithm to determine the best category attribution, and classifying the life state of each life circle to obtain category information of each life circle; and outputting the geographical position information and the category information of each life circle in the first urban area. By using the above scheme, the life state of each life circle can be accurately obtained, and the layout of life circle supporting facilities is more reasonable.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to a data processing method, a method and apparatus for displaying a social circle, and a medium or device. Background Technology

[0002] The "Guidelines for the Construction of 15-Minute Convenience Living Circles in Cities," issued in July 2021, and the subsequent "Regulations on Urban Renewal in the City," have promoted the construction of 15-minute community living circles. A 15-minute convenience living circle refers to a living area with a radius of approximately 1 kilometer and a walking distance of about 15 minutes for residents. The division of these 15-minute convenience living circles facilitates the rational layout of supporting facilities to better meet residents' needs for daily services. However, the aforementioned regulations do not specify how these 15-minute community living circles should be specifically defined.

[0003] Although existing technologies disclose methods for dividing living areas, it is impossible to accurately know the living conditions of each living area after the living areas are defined, which makes it difficult to rationally lay out supporting facilities. Summary of the Invention

[0004] The problem this invention aims to solve is: after dividing living circles, how to accurately obtain the living status of each living circle, so as to provide users with a more convenient and accurate basis for making life decisions?

[0005] To address the above problems, embodiments of the present invention provide a data processing method, the method comprising:

[0006] Obtain road data for the first urban area, POI data for each residential community, and living status data for each residential community;

[0007] Based on the acquired road data and POI data of each community, the living circles of each community are divided to determine the geographical location information of the living circles of each community in the first city area.

[0008] Based on the geographical location information of the living circles of each community and the living status data of each community, a preset clustering analysis algorithm is used to determine the best category affiliation, and the living status of each living circle is classified to obtain the category information of each living circle.

[0009] Output the geographical location information and category information of each living area within the first city area.

[0010] This invention also provides a method for displaying a lifestyle circle, the method comprising:

[0011] When an access request for a living circle is received, the geographical location information and category information of each living circle within the corresponding city area are read from the living circle information database.

[0012] Based on the geographical location information of the living areas, each living area is marked on the electronic map, and the category information of each living area is displayed;

[0013] The information stored in the community information database is obtained using any of the data processing methods described above.

[0014] This invention also provides a data processing apparatus, the apparatus comprising:

[0015] The acquisition unit is suitable for acquiring road data, POI data of each community, and living status data of each community in the first urban area;

[0016] The living circle division unit is suitable for dividing each community into living circles based on the acquired road data and POI data of each community, and determining the geographical location information of the living circle of each community in the first urban area.

[0017] The category determination unit is adapted to determine the best category affiliation based on the geographical location information of the living circle where each community is located and the living status data of each community, and to classify the living status of each living circle to obtain the category information of each living circle.

[0018] The output unit is adapted to output the geographical location information and category information of each living area within the first city area.

[0019] This invention also provides another display device for a living space, the device comprising:

[0020] The reading unit is adapted to read the geographical location information and category information of each living circle within the corresponding city area from the living circle information database when it receives an access request for the living circle;

[0021] The display unit is adapted to identify each living circle on an electronic map based on the geographical location information of the living circle read, and to display the category information to which each living circle belongs;

[0022] The information stored in the community information database is obtained using any of the data processing methods described above.

[0023] This invention also provides an electronic device, which includes any of the above-described data processing devices or the above-described living space display devices.

[0024] This invention also provides a computer storage medium storing a computer program thereon, the computer program being executed by a processor to implement the steps of any of the above methods.

[0025] This invention also provides an electronic device, which includes a memory and a processor. The memory stores a computer program that can run on the processor. The processor executes the steps of any of the methods described above when running the computer program.

[0026] Compared with the prior art, the technical solution of the embodiments of the present invention has the following advantages:

[0027] By applying the solution of this invention, after dividing a first urban area into multiple living circles, and then using the geographical location information of each living circle and the living status data of each community, a preset clustering analysis algorithm is used to determine the optimal category assignment. The living status of each living circle in the first urban area is then classified to obtain the category information of each living circle. Finally, the geographical location information and category information of each living circle in the first urban area are output. Therefore, users can not only know the geographical location of each living circle in the first urban area, but also the living status of each living circle, making it easier for users to make accurate life decisions based on both the geographical location and living status of each living circle, thus providing convenience for users' lives. Attached Figure Description

[0028] Figure 1 This is a flowchart of a data processing method according to an embodiment of the present invention;

[0029] Figure 2 This is a schematic diagram of the cluster analysis process;

[0030] Figure 3 This is a flowchart of a method for displaying a social circle according to an embodiment of the present invention;

[0031] Figure 4 This is a schematic diagram of the structure of a data processing device according to an embodiment of the present invention;

[0032] Figure 5 This is a schematic diagram of the structure of a display device for a living circle according to an embodiment of the present invention;

[0033] Figure 6 This is a schematic diagram showing the distribution of residential areas near the Inner Ring Elevated Road in Shanghai. Detailed Implementation

[0034] Currently, after defining living circles, it is impossible to accurately know the living status of each living circle, which increases inconvenience for users' life decisions.

[0035] To address this problem, this invention provides a data processing method. Applying this method, after dividing a first urban area into multiple living circles, the method further categorizes the living circles based on their geographical location information and the living status data of each residential area. Finally, it outputs the geographical location information and category information of each living circle. Therefore, by using this invention, users can not only know the geographical location of each living circle in the first urban area but also the living status of each circle. This allows users to make accurate life decisions based on both the geographical location and living status of each living circle, thus providing convenience for their lives. For example, it allows for the accurate planning of supporting facilities within each living circle.

[0036] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0037] Reference Figure 1 This invention provides a data processing method, which may include the following steps:

[0038] Step 11: Obtain road data, POI data and living status data for each community in the first urban area.

[0039] In embodiments of the present invention, the first urban area can be any urban area, without any specific limitation. In other words, for any urban area, the data processing method in the embodiments of the present invention can be used to obtain multiple living circles and related information of that urban area.

[0040] In embodiments of the present invention, a residential community refers to a large area of ​​residential housing within a certain urban area that has a relatively independent living environment and is equipped with a complete set of living service facilities, such as commercial outlets and schools (kindergartens).

[0041] In practice, the road data can be obtained using internet information extraction technology.

[0042] In practice, the road data may include a variety of natural geographical factors that can influence people’s behavior, such as urban road data, traffic loop data, overpass location data, and river location data.

[0043] The urban road data may include: road length data, road classification data, road alignment data, road number data, etc. Taking Shanghai as an example, the traffic ring road data may include the geographical location data of the inner ring road, middle ring road, and outer ring road.

[0044] Based on the aforementioned road data, a transportation network for the first urban area can be constructed. Subsequent developments of living areas should avoid being fragmented by the aforementioned natural geographical factors that influence people's behavior.

[0045] In specific implementation, the Point of Interest (POI) data for each community may include: the geographical location information of each building in the community; the number of buildings in the community; the number of residents in each building in the community; and the information on surrounding living facilities in the community.

[0046] The information on surrounding amenities may include: information on the types of amenities, the number of amenities in each type, and the geographical location of each amenity.

[0047] In practice, the aforementioned supporting facilities can be categorized into: basic supporting facilities and commercial supporting facilities. The commercial supporting facilities may include: shopping facilities, catering facilities, daily living facilities, healthcare facilities, educational facilities, hotel facilities, and financial and insurance facilities.

[0048] In practice, shopping service facilities can include shopping malls, shopping centers, supermarkets, and convenience stores. Catering service facilities can include restaurants. Daily life service facilities can include farmers' markets, fresh fruit and vegetable stores, etc. Healthcare service facilities can include hospitals, pharmacies, etc. Educational service facilities can include schools, training institutions, etc. Hotel service facilities can include hotels, guesthouses, etc. Financial and insurance service facilities can include banks, etc. Infrastructure can include subways, bus stations, gas stations, etc.

[0049] For example, information on the surrounding amenities of a residential community may include: 14 shopping facilities, 138 catering facilities, 218 living facilities, 35 healthcare facilities, 75 educational facilities, 19 hotel facilities, 39 financial and insurance facilities, 19 infrastructure facilities, and the geographical location information of the aforementioned amenities.

[0050] In practical implementation, the geographical location information of each building in the community refers to the geographical location of each building within the community. The number of buildings in the community refers to the total number of buildings in the community. The number of households in each building in the community is also included; for example, building A has 20 households, building B has 28 households, etc.

[0051] In specific implementation, the living status data of each community includes: relevant information about housing in the community; green coverage rate information of the community; parking space ratio information of the community; and relevant information about each resident in the community. The relevant information about each resident in the community includes: basic attribute information and consumption-related information of each resident in the community.

[0052] In practice, the relevant information about the housing in the community may include: rent, selling price, property management fees, and building age; the community's green coverage rate, i.e., the percentage of green area to total community area; and the community's parking space ratio, i.e., the ratio between the total number of households and the total number of parking spaces.

[0053] In practice, the relevant information of each resident in the community may include: basic attribute information and consumption-related information of each resident. The basic attribute information may include: the resident's age, marital status, whether they have children, and the children's age and education level. The consumption-related information may include: the amount spent by the resident in restaurants, leisure and entertainment venues, the level of spending at these venues, vehicle purchases, and mobile phone models.

[0054] It should be noted that in practical applications, all consumer venues within the first city area can be pre-classified into multiple tiers, thereby obtaining information on the consumption levels of the venues frequented by residents. For example, based on the average spending per person, consumer venues can be divided into the following five tiers: Tier 1: venues with an average spending of over 2000 yuan per person; Tier 2: venues with an average spending of 1000 to 2000 yuan per person; Tier 3: venues with an average spending of 500 to 1000 yuan per person; Tier 4: venues with an average spending of 100 to 1000 yuan per person; and Tier 5: venues with an average spending of less than 100 yuan per person.

[0055] Step 12: Based on the acquired road data and POI data of each community, divide each community into living circles and determine the geographical location information of the living circles of each community within the first urban area.

[0056] In practice, based on the acquired road data and POI data of each community, various methods can be used to divide each community into living circles, and no restrictions are imposed here.

[0057] In one embodiment of the present invention, the geographical area of ​​each residential community can be determined first based on the road data. Then, density analysis is performed on the communities within each area to obtain density information for each community. Next, the community clusters to which each community belongs are identified. Based on the density information of communities within the same community cluster, the center point of each community cluster is determined. Finally, based on the center point of each community cluster, combined with information on all supporting facilities within a 1km radius of each community, the boundary information of the living area to which each community belongs is determined. The center point of the community cluster is the community with the highest density within that cluster.

[0058] In practice, dividing living circles based on road data can avoid the final division of living circles by traffic ring roads or main roads of the first city. This prevents living circles from being divided by traffic ring roads or main roads of the first city, making the final division of living circles closer to people's actual community behavior and improving the accuracy of living circle division.

[0059] Specifically, when road data includes traffic ring road data, the first urban area can be divided into multiple regions based on this traffic ring road data. For example, when the traffic ring road data includes the geographical location data of the inner ring, middle ring, and outer ring, the first urban area can be divided into three regions: inner ring, middle ring, and outer ring. Thus, density analysis can be performed on each region sequentially to obtain the living circles within each region.

[0060] When road data does not include traffic loop data, the city can be divided into multiple regions based on the main roads of the first city area, and then density analysis can be performed on each region to obtain the living circles within each region.

[0061] In practice, density analysis is conducted on residential communities within each region to obtain density information for each community. This involves counting the number of households in each community within that region; the more households a community has, the higher its density. The number of households in a community can be obtained from the number of buildings within the community and the number of households in each building. For example, if community A has 10 buildings, and each building has 10 households, then community A has a total of 100 households.

[0062] In practice, the term "residential cluster" refers to a group of adjacent residential communities that do not cross city roads. These adjacent communities can consist of at least two communities, but may also include three or four, etc., without limitation. For a single residential community, if there are no adjacent communities that do not cross city roads, no residential area is defined. In other words, the final defined residential area belongs to a residential cluster.

[0063] In practice, the densest neighborhood in a neighborhood cluster can be selected as the center point of that cluster. It should be noted that the neighborhood clusters to which each neighborhood belongs can be identified first, and then density analysis can be performed on each neighborhood within the cluster to determine the center point. This avoids increasing computational load by performing density analysis on neighborhoods that do not constitute a neighborhood cluster.

[0064] In practical implementation, when determining the boundary information of the living circle of each community based on the center point of each community cluster and the information of all living facilities within a 1km radius of each community, we can first determine all living facilities within a 1km radius of the center point of each community cluster, and then determine whether the determined living facilities meet the preset conditions. If the determined living facilities meet the preset conditions, the boundary of the living circle of the community that meets the preset conditions is drawn using the geometric edge-drawing algorithm.

[0065] The preset conditions can be set according to actual living service needs. Communities that meet the preset conditions can basically meet actual living service needs. For example, the preset conditions can be set as follows: within a 1km radius of the community, there should be at least 2 schools, 2 farmers' markets, and 1 shopping mall.

[0066] If the center point of a certain community cluster is community A, and the supporting facilities within 1km of community A include: 2 schools, 1 subway, 1 farmers' market, and 2 shopping malls, then the supporting facilities within 1km of community A do not meet the preset conditions. In this case, even if community A is the center point of the community cluster, it is still not designated as a living circle.

[0067] If the center point of a certain community cluster is community B, and the supporting facilities within 1km of community A include: 2 schools, 1 subway, 2 farmers' markets, and 2 shopping malls, then the supporting facilities within 1km of community A meet the preset conditions. The boundary of the living circle of community B is drawn using the geometric ditch edge algorithm.

[0068] In practical implementation, after drawing the boundary of the living circle for community B using the geometric edge algorithm, road data can be used to further check whether the divided individual living circles cross ring roads or roads. If so, the boundary of the living circle is adjusted to avoid crossing ring roads or roads. Due to the characteristics of the geometric edge algorithm, the living circle boundary obtained by the geometric edge algorithm is usually a road, not inside a community. Furthermore, the final living circle range may exceed or be less than 1 km from the community's perimeter.

[0069] The solution of this invention results in a fragmented, discontinuous living circle, breaking away from traditional circular or grid-based division methods. This approach provides an ecological decoding of the 15-minute convenient living circle, leading to more accurate division. For example, when dividing Shanghai into living circles using this solution, 837 fragmented living circles can be obtained. The distribution of living circles near the inner ring elevated highway in Shanghai is shown below. Figure 6 As shown. Furthermore, when dividing the living areas, information on the surrounding amenities was taken into account, resulting in living areas that are more conducive to the layout of amenities.

[0070] Step 13: Based on the geographical location information of the living circles of each community and the living status data of each community, a preset clustering analysis algorithm is used to determine the best category affiliation, and the living status of each living circle is classified to obtain the category information of each living circle.

[0071] The type of living circle can broadly define the characteristics of that living circle or the living circles in the surrounding area, highlighting their individuality and differentiation.

[0072] In one embodiment of the present invention, the living status data corresponding to each living circle can be obtained first based on the geographical location information of the living circle where each community is located. Then, the K-MEANS clustering analysis algorithm is used to perform clustering analysis on the living status data corresponding to each living circle to determine the best category affiliation. Finally, based on the living status data corresponding to each living circle, the category information of each living circle is determined.

[0073] In practical implementation, the living status data corresponding to each living circle is the average of the living status data of the communities included in each living circle. For example, if a living circle includes community A and community B, then the living status data of that living circle includes: the average of relevant information about housing in community A and community B, the average green coverage rate, and the average parking space ratio.

[0074] Various clustering analysis algorithms can be used to classify the living status of each living circle; no restrictions are imposed here.

[0075] In one embodiment of the present invention, the k-means clustering algorithm (K-MEANS) can be used to classify the living conditions of each living circle. K-MEANS is an iterative clustering algorithm.

[0076] Specifically, we can first divide all living circles into several categories according to the various categories of living status data. The characteristics of each category are described by the mean of the characteristics of the living circle samples within it. This mean is called the centroid, representing the typical profile of the category. After selecting the initial centroid, we repeat the following two steps until the centroid no longer moves significantly, thus obtaining the optimal living circle classification: First, assign each living circle to its nearest centroid; second, create a new centroid by taking the average of all living circles assigned to the previous centroid.

[0077] For example, after selecting the initial centroid, the social circles can be clustered into nine categories from 1 to 9, and a graph can be drawn based on the information contribution. Figure 2 The scree plot shown represents the optimal classification tree. If there are fewer than these inflection points, the classification accuracy is insufficient; if there are more than these inflection points, the differences between categories are not significant.

[0078] Therefore, in the embodiments of this invention, living circles are divided into four categories. Cluster analysis is performed on the living status data according to these four categories to obtain the TGI ranges for multiple indicators corresponding to each category of living circle, including the TGI range for neighborhood grade, consumption level, building age, resident age distribution, and resident education level. Here, TGI refers to the ratio between the current percentage of indicators in the current living circle and the average percentage of current indicators across all living circles. For example, the neighborhood grade TGI range refers to the ratio between the percentage of neighborhood grade A in living circle and the average percentage of neighborhood grades across all living circles.

[0079] In practice, all residential communities within the first city area can be pre-divided into multiple tiers, thereby obtaining tier information for each community. Specifically, based on the living status data of each community, all residential communities within the first city area are divided into multiple tiers, including information related to housing, green coverage rate, parking space ratio, and information about each resident.

[0080] Based on the key characteristics of each type of living circle, the four types are: Affordable; Senior Living; Mature High-Potential; and High-End Refined. Affordable living circles are characterized by low-end neighborhoods, the oldest buildings, and a predominantly young and middle-aged population with relatively low-end spending power. Senior Living: Mature, mid-range neighborhoods are predominantly older, with a high concentration of highly educated seniors and higher spending power. Mature, High-Potential: Mature, mid-to-high-end neighborhoods include both new and established communities, with a balanced distribution of residents in terms of education and age, and relatively high spending power. High-End Refined: The highest-end neighborhoods are predominantly young adults, with the highest average education level and the highest spending power.

[0081] In practice, after determining the category of each living circle, statistics can be compiled on the types of living circles within the first urban area to obtain the proportion of each type and output the proportion of each type of living circle. For example, when dividing living circles in Shanghai, 837 "fragmented" living circles can be obtained. Among them, the proportion of economical and affordable living circles is 42%, the proportion of senior-oriented quality living circles is 16%, the proportion of mature and high-potential living circles is 27%, and the proportion of high-end and refined living circles is 15%.

[0082] Step 14: Output the geographical location information and category information of each living circle within the first city area.

[0083] In practice, the geographical location information and category information of each living circle within the first city area can be output in various ways, without any restrictions. For example, the geographical location information and category information of each living circle can be generated into a file, and the information of the living circles within the first city area can be obtained by viewing the file corresponding to each living circle.

[0084] In one embodiment of the present invention, to improve the efficiency of acquiring living area information, the geographical location information and category information of each living area within the first city area can be output on an electronic map. Specifically, based on the geographical location information of each living area, each living area can be identified on the electronic map, including drawing the scope of the living area on the electronic map and displaying the name of each living area. Simultaneously, the category information of each living area can also be displayed on the electronic map. Specific implementation can be referred to the description of the living area display method, which will not be repeated here.

[0085] In one embodiment of the present invention, the method may further include: calculating and outputting consumption capacity information of each living circle based on consumption-related information of each resident in the community.

[0086] As described above, the consumption-related information of each resident in the community may include: the amount spent by residents in restaurants, leisure and entertainment venues, the level of spending at the venues they frequent, vehicle expenses, mobile phone models, and other information. In some embodiments, information such as housing prices in the resident's place of residence may also be included.

[0087] In practical implementation, consumption information related to residents within the first urban area can be comprehensively integrated, and a multi-dimensional model can be trained using a comprehensive model method to obtain the final consumption level assessment model. After obtaining consumption information related to each resident in each community, the consumption information of residents in each community within each living circle can be summarized to obtain the consumption information of residents within each living circle. Then, using the consumption level assessment model, the consumption level value of each living circle can be obtained. The consumption level values ​​of each living circle within the first urban area are categorized into tiers to determine the corresponding consumption level range for each tier. By categorizing consumption levels, the distribution of consumption levels of the entire city's population can be obtained.

[0088] For example, the consumption level of the first city area can be divided into 5 levels, with the top 10% as the highest level, the top 11% to 30% as the second highest level, the top 31% to 60% as the middle level, the top 61% to 80% as the second lowest level, and the top 81% to 100% as the lowest level.

[0089] After obtaining consumption-related information for each resident in each community of a certain living area, a consumption level assessment model can be used to obtain the consumption level value of that living area. This value is then compared with consumption level tiers to determine the consumption capacity of the living area. The consumption capacity information of the living area can include not only the overall consumption level tier of the living area, but also an analysis of the residents to determine the proportion of people corresponding to each consumption level tier.

[0090] For example, the consumption power information of a certain living circle can include: the overall consumption level of the living circle is the third level, the proportion of people with the highest consumption level is 6%, the proportion of people with the second highest consumption level is 20%, the proportion of people with the middle consumption level is 30%, the proportion of people with the second lowest consumption level is 30%, and the proportion of people with the lowest consumption level is 14%.

[0091] Information on the spending power of a living area can more accurately reflect the living conditions of that area, which is more conducive to the rational planning of supporting facilities. For example, supporting facilities that match the spending power of the residents can be configured around the living area.

[0092] In another embodiment of the present invention, the method may further include: obtaining and outputting population profile information of residents in each living circle based on the basic attribute information of each resident in the community.

[0093] As mentioned above, the basic attribute information of each resident in the community may include: the resident's age, marital status, whether they have children, and the children's age and education level. In some embodiments, it may also include information such as the resident's current life stage and application preferences.

[0094] By statistically analyzing the basic attribute information of residents in each community within the same living circle, corresponding statistical results can be obtained. For example, population type information of the living circle can be obtained (including the number of permanent residents, marital status, children's ages and education levels, gender ratio information, age distribution information, etc.). The obtained statistical results can be used as population profile information of residents within the living circle.

[0095] Information about the population profiles of residents within a neighborhood is more helpful in rationally planning supporting facilities. For example, facilities suitable for the age groups of most residents can be located around the neighborhood.

[0096] In other embodiments of the present invention, a recommendation index for each living circle can also be output. The recommendation index of a living circle is used to characterize the commercial potential of that living circle and to guide the deployment of commercial facilities around that living circle.

[0097] In specific implementation, the following method can be used to obtain the recommendation index of each living circle: Based on the relevant information of each resident in the community and the information of the surrounding living facilities, determine the relevant information of the residents in each living circle and the information of the living facilities included in each living circle; use factor analysis algorithm to reduce the dimensionality of the relevant information of the residents in each living circle and the information of the living facilities included in each living circle to determine the common factors of each living circle; based on the common factors of each living circle, calculate and output the recommendation index of each living circle.

[0098] In practical implementation, the relevant information for each resident in the community may include: the community's population size. Based on the community's population size, the population size of each living area can be determined. The relevant information for each resident may also include: consumption-related information and basic attribute information for each resident within the community. Based on the consumption-related information and basic attribute information for each resident within the community, the population quality of the community can be obtained.

[0099] In practice, based on the information on the basic supporting facilities around the community, the basic supporting facilities around the living area can be obtained.

[0100] In specific implementation, the information on commercial facilities surrounding the residential area may include: Points of Interest (POI) data for independent basic businesses; POI data for chain brand businesses; POI data for well-known brand businesses; and POI data for emerging brands. Specifically, the POI data for independent basic businesses can be the number of farmers' markets, fruit shops, etc. The POI data for chain brand businesses can be the number of businesses with more than 10 chain stores nationwide. The POI data for well-known brand businesses can be the number of businesses with fewer than 10 stores nationwide. The POI data for emerging brands can be the number of brands that have appeared in the last two years.

[0101] Factor analysis is a statistical method used to extract common factors from a group of variables. It can identify hidden, representative factors among many variables. Grouping variables with similar characteristics into a single factor reduces the number of variables and allows for testing hypotheses about the relationships between them.

[0102] In embodiments of the present invention, factor analysis algorithms can be used to reduce the dimensionality of information related to residents in each living circle and information on supporting facilities included in each living circle, thereby determining common factors of each living circle.

[0103] Specifically, information about residents within each living circle and the supporting facilities within each living circle can be grouped into a single factor based on shared characteristics. For example, population data for each living circle can be categorized as a population factor. Basic supporting facilities around the living circle can be categorized as a basic supporting facilities factor. POI data for independent basic businesses, chain brand businesses, and well-known brand businesses within the living circle can be categorized as a brand atmosphere factor. POI data for well-known brand businesses within the living circle can be categorized as a development potential factor.

[0104] After obtaining the above common factors, the recommendation index for each living circle can be obtained by using factor analysis.

[0105] In some embodiments, the average recommendation index of all living areas can be taken to obtain the average recommendation index of the first urban area living area. When outputting the living area recommendation index, the average recommendation index of the first urban area living area can also be output simultaneously. Of course, the highest and lowest recommendation indices of the first urban area living area can also be output to meet personalized needs.

[0106] In practice, information such as the spending power of residents within a neighborhood, resident demographics, and recommendation indices can also be displayed on the electronic map. For details, please refer to the description of the neighborhood display method.

[0107] As described above, the data processing method in this embodiment of the invention, after dividing living areas, can also output category information, consumption capacity information, resident profile information, and recommendation index of the living areas. Based on the above information, the living status of each living area can be more accurately understood, thereby enabling more accurate life decisions and providing convenience for users. For example, it can better guide the rational layout of supporting facilities.

[0108] Reference Figure 3 This invention also provides a method for displaying a social circle, which can be executed by a social circle display device. Specifically, the method may include the following steps:

[0109] Step 31: When an access request for a living circle is received, the geographical location information and category information of each living circle within the corresponding city area are read from the living circle information database.

[0110] The information stored in the community information database is obtained using the data processing method described in the above embodiments.

[0111] In one embodiment, the community information database only includes the geographical location information and category information of each community.

[0112] In another embodiment, the living circle information database may also store other information about the living circle, such as one or more of the following: the living circle's spending power information, the living circle's recommendation index, the number of living facilities in the living circle, and the population profile information of residents within the living circle. For example, the living circle information database may simultaneously store the living circle's spending power information, the living circle's recommendation index, the number of living facilities in the living circle, and the population profile information of residents within the living circle.

[0113] In practice, the access request for the "life circle" can be an access request for a webpage sent by the user terminal or an access request for an application sent by the user terminal; there is no specific restriction.

[0114] Upon receiving an access request for the aforementioned living area, the system retrieves the geographical location and category information of each living area within the corresponding city region from the living area information database. The corresponding city region can be a default city region or the city region where the user is currently located. The user's current city region can be determined by locating the location where the user sent the access request.

[0115] In some embodiments, the access request for the living area may carry indication information of a city area identifier. In this case, the corresponding city area may be the city area indicated by the indication information of the city area identifier.

[0116] In some embodiments, upon receiving an access request for the community, the user's identity can be verified first. Only after the user's identity is verified can each community be marked on the electronic map, and the category information of each community be displayed, thereby improving the security of the community information. For example, the user may need to enter the correct account and password before being allowed to view the community information.

[0117] In practice, the community information database can be located locally or on a remote server; there are no specific restrictions. Regardless of its location, information can be retrieved from the community information database.

[0118] Step 32: Based on the read geographical location information of the living areas, mark each living area on the electronic map and display the category information of each living area.

[0119] An electronic map, also known as a digital map, is a map stored and viewed digitally using computer technology. Electronic maps typically store information using vector graphics, and the map scale can be enlarged, reduced, or rotated without affecting the display. An electronic map is a system for map creation and application; it is a map generated under computer control, a screen map based on digital cartography technology, and a visualized physical map. "Visualization on a computer screen" is the fundamental characteristic of electronic maps.

[0120] After reading the geographical location information of each living area, the system marks each living area on an electronic map, including its location and name. The boundaries of the living areas marked on the electronic map are irregular shapes.

[0121] Specifically, based on the geographical location information of a living area, corresponding designated points can be found on an electronic map. Finally, all designated points within the same living area are connected to obtain the boundary shape of the living area. The boundary shapes of the living areas marked on the electronic map are irregular shapes, unlike existing regular shapes such as circles or grids. After obtaining the boundary shapes of each living area, a map of that living area can be obtained.

[0122] In some embodiments, along with identifying the name of a neighborhood, the category to which the neighborhood belongs can be displayed. For example, the boundary of each neighborhood can be outlined with a line of a specific color, and the corresponding name and category can be displayed at the edge of the neighborhood. The color of the boundaries of each neighborhood can be the same, or different colors can be set based on the street or town where they are located. In this way, users can more intuitively understand the location of the neighborhood and its corresponding living status when viewing it.

[0123] Compared to viewing individual life circles by opening files one by one, displaying life circles on an electronic map reduces user operations and provides different display effects as the electronic map is zoomed in, zoomed out, and rotated, meeting different user needs.

[0124] In some embodiments, the community information database may also store other information about each community within the corresponding urban area. In this case, the method may further include:

[0125] When a living circle indication message is received, other information about each living circle within the corresponding city area is read from the living circle information database, and the other information about the living circle indicated by the living circle indication message is displayed on the page where the electronic map is located.

[0126] The other information of the living circle includes at least one of the following: the living circle's consumption capacity information, the living circle's recommendation index, the number of living facilities in the living circle, the population profile information of residents in the living circle, and the distribution information of service outlets in the living circle.

[0127] To make the displayed page clearer, in embodiments of the present invention, the user terminal can send community indicator information. In some embodiments, the community indicator information may include an identifier of a community; for example, when a user double-clicks a community on the electronic map display page, the community indicator information will be sent.

[0128] In practice, the network distribution information may include information on supporting living facilities and other information. The information on supporting living facilities in the living circle may be a summary of the supporting living facilities around each community included in the living circle. Similar to the information on supporting living facilities around communities, it can also be divided into basic supporting facilities information and commercial supporting facilities information.

[0129] The commercial supporting facilities may include: shopping service facilities, catering service facilities, living service facilities, medical and healthcare service facilities, educational service facilities, hotel service facilities, and financial and insurance service facilities. The information on commercial supporting facilities may include the geographical location and quantity information of various commercial supporting facilities. The information on basic supporting facilities may include the geographical location and quantity information of various basic supporting facilities.

[0130] The other information may include information about residential communities and office buildings. Residential community information includes the geographical location and number of each community. Office building information includes the geographical location and number of office buildings.

[0131] By analyzing the network distribution information, one can understand the commercial development of the living area and track its commercial development year by year to know the balance of the distribution of business types (infrastructure, commerce, catering) within the living area (whether any of them are missing).

[0132] After receiving the community information, detailed information about the community can be displayed on a separate layer of the current page. This includes: the community's spending power, recommendation index, number of amenities, resident demographics, and service point distribution. Each type of information can be assigned a tab, allowing users to access more detailed information within that tab.

[0133] For example, users can select the "Spending Power" tab, which will display spending power information for that neighborhood. Users can also select "User Profile," which will display user profile information for that neighborhood.

[0134] When a user selects the "Location Distribution" tab, in one embodiment, the display device of the living area can determine the number of each location within each living area based on the geographical location information of each location by reading the location distribution information, and display the quantity information of each location under the "Location Distribution" tab. Alternatively, it can also display the geographical location information of each location simultaneously. In another embodiment, the location distribution information in the living area information database can only store the quantity of each type of location, without storing the geographical location information. In this case, the display device of the living area can directly display the quantity information of each type of location under the "Location Distribution" tab by reading the location distribution information, without needing to calculate the quantity of each type of location within each living area.

[0135] In practice, the display device for the living circles can not only provide an overview of all living circles within a certain city area and view information about individual living circles, but also filter and analyze living circles.

[0136] In one embodiment of the present invention, the display device of the social circle can receive social circle filtering information sent by the user. The social circle filtering information may include filtering conditions, which may be multiple, such as "social circle recommendation index greater than 70" or "the proportion of high-consumption people greater than 40%".

[0137] The filtering criteria can be entered in various ways. For example, corresponding tabs can be set on the display page, each tab has multiple options, and users can choose to enter the corresponding options under certain tabs as the filtering criteria.

[0138] In practice, after receiving the filtering information of the social circle, the display device of the social circle can read the original information from the social circle information database and analyze the original information to output the corresponding analysis results.

[0139] For example, if the filtering condition is "the proportion of high-spending people is greater than 40%", then the display device of the living circle can read the consumption capacity information of each living circle from the living circle information database, calculate the proportion of high-spending people in each living circle, and filter out the identifiers of living circles where the proportion of high-spending people is greater than 40%.

[0140] In one embodiment of the present invention, the display device of the living circle can also analyze the basic situation and business situation of the living circle within a certain range based on user input.

[0141] For example, the display device for the living circle can analyze the basic situation within a community. Specifically, it can retrieve relevant information from the community's living circle information database, including living circle type, resident information, and recommendation index. The output analysis results may include: living circle type, population size, recommendation index, percentage of high-spending residents, percentage of families with children, and percentage of registered residents aged 60 and above. While outputting the above analysis results, it can also compare them with automatically averaged data for the city or district. Of course, the specific analysis results can include other content, which is not limited here. Through analysis, users can understand the missing or underdeveloped service industries within the community.

[0142] It should be noted that the analysis results can be presented in text form or in a combination of tables and electronic maps; there are no restrictions here.

[0143] For example, the display device for the living circle can analyze the types of living circles within a certain range to obtain the specific situation of the types of living circles within that range. It can also compare them with the types of living circles in the district or city where they are located, thereby enabling users to understand the specific ranking of the living circles within that range and their relative level with the city as a whole.

[0144] It is understood that, in the embodiments of the present invention, the results of the analysis of the living circle can be displayed in a variety of ways, which will not be illustrated here.

[0145] As can be seen from the above, the method for displaying living areas in this embodiment of the invention, by displaying the information of living areas on an electronic map, makes it easier for users to view and allows them to obtain relevant information about living areas more intuitively, effectively reducing user operations. Furthermore, based on user input, the corresponding living area information can be analyzed to improve viewing efficiency and better guide the rational layout of facilities.

[0146] To enable those skilled in the art to better understand and implement the present invention, the apparatus corresponding to the above-described method is described in detail below.

[0147] Reference Figure 4 This invention also provides a data processing device, comprising: an acquisition unit 41, a living area segmentation unit 42, a category determination unit 43, and an output unit 44. Wherein:

[0148] The acquisition unit 41 is adapted to acquire road data of the first urban area, POI data of each community, and living status data of each community.

[0149] The living circle division unit 42 is adapted to divide each community into living circles based on the acquired road data and POI data of each community, and determine the geographical location information of the living circle of each community in the first urban area.

[0150] The category determination unit 43 is adapted to determine the best category affiliation based on the geographical location information of the living circle where each community is located and the living status data of each community, and to classify the living status of each living circle to obtain the category information of each living circle.

[0151] The output unit 44 is adapted to output the geographical location information and category information of each living circle within the first urban area.

[0152] In one embodiment of the present invention, the living status data includes: relevant information about housing in the community; green coverage information of the community; parking space ratio information of the community; and relevant information about each resident in the community. The relevant information about each resident in the community includes: basic attribute information and consumption-related information of each resident in the community.

[0153] In one embodiment of the present invention, the device may further include: a consumption capacity calculation unit 45. The consumption capacity calculation unit 45 is adapted to calculate the consumption capacity information of each living area based on the consumption-related information of each resident in the community;

[0154] The output unit 44 is also adapted to output consumption capacity information for each living circle.

[0155] In one embodiment of the present invention, the device may further include: a population profile statistics unit 46. The population profile statistics unit 46 is adapted to obtain population profile information of residents within each living circle based on the basic attribute information of each resident in the community. The output unit 44 is further adapted to output the population profile information of residents within each living circle.

[0156] In one embodiment of the present invention, the POI data of each community includes: geographical location information of each building in the community; number of buildings in the community; number of residents in each building in the community; and information on surrounding living facilities.

[0157] In one embodiment of the present invention, the information on supporting facilities around the community includes: information on basic supporting facilities around the community and information on commercial supporting facilities around the community; the living status data includes: relevant information of each resident in the community; the relevant information of each resident in the community includes: basic attribute information and consumption-related information of each resident in the community;

[0158] The device further includes a recommendation index calculation unit 47. The recommendation index calculation unit 47 is adapted to determine the relevant information of residents within each living circle and the information of living facilities included in each living circle based on the relevant information of each resident in the community and the information of living facilities surrounding the community; to reduce the dimensionality of the relevant information of residents within each living circle and the information of living facilities included in each living circle using a factor analysis algorithm; to determine the common factors of each living circle; and to calculate the recommendation index of each living circle based on the common factors of each living circle.

[0159] Accordingly, the output unit 44 is also adapted to output the recommendation index of each living circle and store it in the living circle information database.

[0160] The specific implementation of each functional unit of the data processing device can be referred to the above description of the data processing method, and will not be repeated here.

[0161] Reference Figure 5 This invention also provides a display device for a living space, the device comprising: a reading unit 51 and a display unit 52. Wherein:

[0162] The reading unit 51 is adapted to read the geographical location information and category information of each living circle within the corresponding urban area from the living circle information database when it receives an access request for the living circle.

[0163] The display unit 52 is adapted to identify each living circle on an electronic map based on the read geographical location information of the living circle, and to display the category information to which each living circle belongs.

[0164] The information stored in the community information database is obtained using the data processing method described above.

[0165] In specific implementation, the reading unit 51 can also read other information from the community information database, and the display unit 52 can also display the corresponding information on the electronic map page. For specific implementation, please refer to the above description of the display method of the community.

[0166] This invention also provides an electronic device, which includes the data processing device or the living circle display device described above.

[0167] This invention also provides another electronic device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the steps of the above method when running the computer program.

[0168] In practical implementation, users can input corresponding commands into the electronic device via an input device, causing the electronic device to perform specific functions. When the electronic device includes a display device for the living space, it is a device with a display screen and capable of human-computer interaction. The electronic device can display a user interface through the display screen. Examples include smart home terminals (including air conditioners, refrigerators, rice cookers, water heaters, etc.), smart business terminals (including video phones, smart conference desktop terminals, etc.), wearable devices (including smartwatches, smart glasses, etc.), financial smart terminals, as well as smartphones, tablets, personal digital assistants (PDAs), in-vehicle devices, computers, etc.

[0169] This invention also provides a computer storage medium storing a computer program thereon, which is executed by a processor to implement the steps of the above method.

[0170] In specific implementations, the computer-readable storage medium may include ROM, RAM, disk, or optical disk, etc.

[0171] Regarding the modules / units included in the various devices and products described in the above embodiments, they can be software modules / units, hardware modules / units, or a combination of both. For example, for various devices and products applied to or integrated into a chip, all of their modules / units can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs that run on a processor integrated within the chip, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits; for various devices and products applied to or integrated into a chip module, all of their modules / units can be implemented using hardware methods such as circuits, and different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using hardware methods such as circuits. The components can be implemented using software programs that run on the processor integrated within the chip module. The remaining (if any) modules / units can be implemented using hardware methods such as circuits. For various devices and products applied to or integrated into the terminal, each of its components / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or in different components within the terminal. Alternatively, at least some modules / units can be implemented using software programs that run on the processor integrated within the terminal, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits.

[0172] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A data processing method, characterized in that, include: Obtain road data for the first urban area, POI data for each residential community, and living status data for each residential community; Based on the acquired road data and POI data of each community, the living circles of each community are divided to determine the geographical location information of the living circles of each community within the first city area. This includes: determining the region where each community is located based on the road data, avoiding the segmentation of living circles by the traffic ring roads or main roads of the first city; performing density analysis on the communities within each region to obtain the density information of each community; identifying the community clusters to which each community belongs; determining the center point of each community cluster based on the density information of the communities within the same community cluster; the center point of the community cluster is the community with the highest density within the community cluster; and determining the boundary information of the living circle of each community based on the center point of each community cluster and combined with the information of all living facilities within a 1km radius of each community. Based on the geographical location information of the living circles of each community and the living status data of each community, a preset clustering analysis algorithm is used to determine the best category affiliation, and the living status of each living circle is classified to obtain the category information of each living circle. Output the geographical location information and category information of each living area within the first city area; The living status data includes: information related to housing in the community; information on the green coverage rate of the community; information on the parking space ratio of the community; and information related to each resident in the community. The information related to each resident in the community includes: basic attribute information and consumption-related information of each resident. The process of determining the boundary information of the living circle of each community based on the center point of each community group and the information of all living facilities within a 1km radius of each community includes: determining all living facilities within a 1km radius of the center point of each community group; determining whether the determined living facilities meet the preset conditions; and drawing the boundary of the living circle of the community that meets the preset conditions using a geometric outlining algorithm when the determined living facilities meet the preset conditions, otherwise not dividing the living circle.

2. The data processing method as described in claim 1, characterized in that, The POI data for each community includes: the geographical location information of each building in the community; the number of buildings in the community; the number of residents in each building in the community; and the information on surrounding living facilities.

3. The data processing method as described in claim 1, characterized in that, The categories of the aforementioned lifestyle circles include: economical and practical; high-quality for seniors; mature and high-potential; and high-end and refined.

4. The data processing method as described in claim 1, characterized in that, Also includes: Based on the consumption-related information of each resident in the community, the consumption capacity information of each living area is calculated and output.

5. The data processing method as described in claim 1, characterized in that, Also includes: Based on the basic attribute information of each resident in the community, population profile information of residents in each living circle is obtained and output.

6. The data processing method as described in claim 3, characterized in that, The information on surrounding amenities includes: basic amenities and commercial amenities. The method further includes: Based on the relevant information of each resident in the community and the information of the surrounding living facilities, the relevant information of each living circle and the information of the living facilities included in each living circle are determined. Using factor analysis algorithms, the dimensionality of information on residents within each living circle and the information on supporting facilities included in each living circle is reduced to determine the common factors of each living circle. Based on the common factors of each living circle, the recommendation index of each living circle is calculated and output.

7. The data processing method as described in claim 6, characterized in that, The common factors of each living circle include: population size, basic infrastructure, brand atmosphere, population quality, and development potential.

8. The data processing method as described in claim 6, characterized in that, The information on commercial facilities surrounding the residential area includes: POI data of independent basic businesses around the residential area; POI data of chain brand businesses; POI data of well-known brand businesses; and POI data of emerging brands.

9. The data processing method as described in claim 1, characterized in that, Based on the geographical location information of the living circles of each community and the living status data of each community, a preset clustering analysis algorithm is used to determine the best category assignment, and the living status of each living circle is classified to obtain the category information of each living circle, including: Based on the geographical location information of the living circles of each community, the living status data corresponding to each living circle is obtained; the K-MEANS clustering analysis algorithm is used to perform cluster analysis on the living status data corresponding to each living circle to determine the best category assignment; based on the living status data corresponding to each living circle, the category information of each living circle is determined.

10. A method for displaying a social circle, characterized in that, include: When an access request for a living circle is received, the geographical location information and category information of each living circle within the corresponding city area are read from the living circle information database. Based on the geographical location information of the living areas, each living area is marked on the electronic map, and the category information of each living area is displayed; The information stored in the community information database is obtained using the data processing method described in any one of claims 1 to 9.

11. The method for displaying a living circle as described in claim 10, characterized in that, When the community information database also stores other information about each community within the corresponding urban area, the method further includes: When a living circle indication message is received, other information about each living circle within the corresponding city area is read from the living circle information database, and other information about the living circle indicated by the living circle indication message is displayed on the page where the electronic map is located. The other information of the living circle includes at least one of the following: the living circle's consumption capacity information, the living circle's recommendation index, the number of living facilities in the living circle, the population profile information of residents in the living circle, and the distribution information of service outlets.

12. The method for displaying a living circle as described in claim 11, characterized in that, After receiving an access request from a community, and before marking each community on the electronic map and displaying the category information of each community, the process also includes: verifying the user's identity; User identity is verified. Once the user's identity is verified, each living circle is marked on the electronic map, and the category information of each living circle is displayed.

13. A data processing apparatus, characterized in that, include: The acquisition unit is suitable for acquiring road data, POI data of each community, and living status data of each community in the first urban area; The living circle segmentation unit is suitable for dividing each community into living circles based on the acquired road data and POI data of each community, determining the geographical location information of the living circle of each community within the first city area. Specifically, it is suitable for determining the region where each community is located based on the road data, avoiding the segmentation of living circles by the traffic ring roads or main roads of the first city; performing density analysis on the communities within each region to obtain the density information of each community; identifying the community groups to which each community belongs; determining the center point of each community group based on the density information of the communities within the same community group; the center point of the community group is the community with the highest density within the community group; and determining the boundary information of the living circle of each community based on the center point of each community group and the information of all living facilities within a 1km radius of each community. The category determination unit is adapted to determine the best category affiliation based on the geographical location information of the living circle where each community is located and the living status data of each community, and to classify the living status of each living circle to obtain the category information of each living circle. The output unit is adapted to output the geographical location information and category information of each living area within the first city area; The living status data includes: information related to housing in the community; information on the green coverage rate of the community; information on the parking space ratio of the community; and information related to each resident in the community. The information related to each resident in the community includes: basic attribute information and consumption-related information of each resident. The process of determining the boundary information of the living circle of each community based on the center point of each community group and the information of all living facilities within a 1km radius of each community includes: determining all living facilities within a 1km radius of the center point of each community group; determining whether the determined living facilities meet the preset conditions; and drawing the boundary of the living circle of the community that meets the preset conditions using a geometric outlining algorithm when the determined living facilities meet the preset conditions, otherwise not dividing the living circle.

14. The data processing apparatus as claimed in claim 13, characterized in that, Also includes: The consumption capacity calculation unit is adapted to calculate the consumption capacity information of each living circle based on the consumption-related information of each resident in the community. The output unit is also adapted to output consumption capacity information for each living circle.

15. The data processing apparatus as claimed in claim 13, characterized in that, Also includes: The population profiling statistical unit is suitable for obtaining population profile information of residents in each living circle based on the basic attribute information of each resident in the community; The output unit is also adapted to output population profile information of residents in each living circle.

16. The data processing apparatus as claimed in claim 13, characterized in that, The POI data for each community includes: the geographical location information of each building in the community; the number of buildings in the community; the number of residents in each building in the community; and the information on surrounding living facilities.

17. The data processing apparatus as claimed in claim 16, characterized in that, The information on surrounding amenities includes: basic amenities and commercial amenities. The device further includes: a recommendation index calculation unit, adapted to determine the relevant information of residents in each living circle and the information of living facilities included in each living circle based on the relevant information of each resident in the community and the information of living facilities around the community; to reduce the dimensionality of the relevant information of residents in each living circle and the information of living facilities included in each living circle using a factor analysis algorithm; to determine the common factors of each living circle; and to calculate the recommendation index of each living circle based on the common factors of each living circle. The output unit is also adapted to output the recommendation index of each living circle and store it in the living circle information database.

18. The data processing apparatus as claimed in claim 13, characterized in that, The category determination unit is adapted to obtain living status data corresponding to each living circle based on the geographical location information of the living circle where each community is located; to perform cluster analysis on the living status data corresponding to each living circle using the K-MEANS clustering analysis algorithm to determine the best category affiliation; and to determine the category information of each living circle based on the living status data corresponding to each living circle.

19. A display device for a living space, characterized in that, include: The reading unit is adapted to read the geographical location information and category information of each living circle within the corresponding city area from the living circle information database when it receives an access request for the living circle; The display unit is adapted to identify each living circle on an electronic map based on the geographical location information of the living circle read, and to display the category information to which each living circle belongs; The information stored in the community information database is obtained using the data processing method described in any one of claims 1 to 9.

20. The display device for a living space as described in claim 19, characterized in that, The boundaries of the living areas marked on the electronic map are irregular shapes.

21. An electronic device, characterized in that, It includes the data processing apparatus according to any one of claims 13 to 18, or the display apparatus including the living circle according to claim 19 or 20.

22. A computer storage medium having a computer program stored thereon, characterized in that, The computer program is executed by a processor to implement the steps of the method according to any one of claims 1 to 12.

23. An electronic device comprising a memory and a processor, wherein the memory stores a computer program capable of running on the processor, characterized in that, When the processor runs the computer program, it performs the steps of the method according to any one of claims 1 to 12.

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