CN114911966A

CN114911966A - Method, apparatus, device and storage medium for house type data processing

Info

Publication number: CN114911966A
Application number: CN202210515758.3A
Authority: CN
Inventors: 方凯能
Original assignee: Beijing Youzhuju Network Technology Co Ltd
Current assignee: Beijing Youzhuju Network Technology Co Ltd
Priority date: 2022-05-11
Filing date: 2022-05-11
Publication date: 2022-08-16

Abstract

According to an embodiment of the present disclosure, a method, an apparatus, a device, and a storage medium for house type data processing are provided. The house type data processing method comprises the steps of obtaining first vector diagram data of a first house type and second vector diagram data of a second house type, wherein the first vector diagram data and the second vector diagram data respectively indicate attribute information of house elements in the first house type and the second house type. The method further comprises the following steps: determining the similarity of the house type between the first house type and the second house type by comparing the first vector diagram data with the second vector diagram data; and determining a processing operation for at least one of the first vector graphics data and the second vector graphics data based on the house type similarity. Therefore, the similarity of the house types can be measured with lower resource consumption and better accuracy, and subsequent operations aiming at the vector diagram data are realized based on the similarity.

Description

Method, apparatus, device and storage medium for house type data processing

Technical Field

Example embodiments of the present disclosure relate generally to the field of computers, and more particularly, to a method, apparatus, device, and computer-readable storage medium for house-type data processing.

Background

The house map can indicate the spatial layout of the house, the depiction of the location, area, shape, etc. of each space in the house. In the related industry of real estate, as basic data for developing multiple services, drawing, management and maintenance of house type diagrams and the like are very important links. For example, in the house renting and selling industry, it is desirable to present a family plan of houses to be rented or sold. In the industries of house decoration, house modeling and the like, the house type graph of a house is also required to be used as a basic material so as to present decoration effect, modeling effect and the like.

Disclosure of Invention

According to an example embodiment of the present disclosure, a scheme for house type data processing is provided.

In a first aspect of the disclosure, a method of house type data processing is provided. The method comprises the following steps: acquiring first vector diagram data of a first house type and second vector diagram data of a second house type, wherein the first vector diagram data and the second vector diagram data respectively indicate attribute information of house elements in the first house type and the second house type; determining the similarity of the house type between the first house type and the second house type by comparing the first vector diagram data with the second vector diagram data; and determining a processing operation for at least one of the first vector graphics data and the second vector graphics data based on the house type similarity.

In a second aspect of the disclosure, an apparatus for house type data processing is provided. The device includes: a data acquisition module configured to acquire first vector diagram data of a first dwelling type and second vector diagram data of a second dwelling type, the first vector diagram data and the second vector diagram data indicating attribute information of house elements in the first dwelling type and the second dwelling type, respectively; a similarity determination module configured to determine a house type similarity between the first house type and the second house type by comparing the first vector diagram data and the second vector diagram data; and a processing determination module configured to determine a processing operation for at least one of the first vector graphics data and the second vector graphics data based on the house type similarity.

In a third aspect of the disclosure, an electronic device is provided. The apparatus comprises at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit. The instructions, when executed by the at least one processing unit, cause the apparatus to perform the method of the first aspect.

In a fourth aspect of the disclosure, a computer-readable storage medium is provided. The computer readable storage medium has stored thereon a computer program executable by a processor to implement the method of the first aspect.

It should be understood that the statements herein set forth in this summary are not intended to limit the essential or critical features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:

FIG. 1 illustrates a schematic diagram of an example environment in which embodiments of the present disclosure can be implemented;

FIG. 2 illustrates a flow diagram of a process for house type data processing according to some embodiments of the present disclosure;

figure 3 illustrates a schematic diagram of an example data structure of vector graphics data, in accordance with some embodiments of the present disclosure;

FIG. 4 illustrates an example of house type data stored in a house type gallery in accordance with some embodiments of the present disclosure;

FIG. 5 illustrates a flow diagram of a vector graphics data based house type deduplication process, according to some embodiments of the present disclosure;

FIGS. 6A and 6B illustrate a flow diagram of a vector graphics data-based house type query process, according to some embodiments of the present disclosure;

FIGS. 7A and 7B illustrate examples of a user-type diagram according to some embodiments of the present disclosure;

FIG. 8 illustrates a block diagram of an apparatus for house-type data processing, in accordance with some embodiments of the present disclosure; and

FIG. 9 illustrates a block diagram of a device capable of implementing various embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are illustrated in the accompanying drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more complete and thorough understanding of the disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.

In describing embodiments of the present disclosure, the terms "include" and its derivatives should be interpreted as being inclusive, i.e., "including but not limited to. The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions are also possible below.

It will be appreciated that the data involved in the subject technology, including but not limited to the data itself, the acquisition or use of the data, should comply with the requirements of the corresponding laws and regulations and related regulations.

It is understood that before the technical solutions disclosed in the embodiments of the present disclosure are used, the type, the use range, the use scene, etc. of the personal information related to the present disclosure should be informed to the user and obtain the authorization of the user through an appropriate manner according to the relevant laws and regulations.

For example, when responding to the receiving of the user's active request, prompt information is sent to the user to explicitly prompt the user that the operation requested to be performed will require acquisition and use of personal information to the user, so that the user can autonomously select whether to provide personal information to software or hardware such as an electronic device, an application program, a server, or a storage medium that performs the operations of the disclosed technical solution according to the prompt information.

As an optional but non-limiting implementation manner, in response to receiving an active request of the user, the prompt information is sent to the user, for example, a pop-up window manner may be used, and the prompt information may be presented in a text manner in the pop-up window. In addition, a selection control for providing personal information to the electronic device by the user selecting "agree" or "disagree" can be carried in the pop-up window.

It is understood that the above notification and user authorization process is only illustrative and not limiting, and other ways of satisfying relevant laws and regulations may be applied to the implementation of the present disclosure.

FIG. 1 illustrates a schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented. In this example environment 100, a computing device 110 may collect, maintain, and manage house pattern data related to houses in one or more buildings 120. The house graph data may be stored in a house graph library 130.

In different application scenarios, different operations may need to be performed for the floor plan. The computing device 110 may be configured to perform corresponding processing as needed by the application scenario to provide the user-type graph-related processing results 112.

For example, during the family mapping phase, the computing device 110 may generate or otherwise obtain new family graph data and manage the family data in the family gallery 130. In the application stage of the house layout, the computing device 110 may perform processing operations such as house type search, house layout rendering with different visual styles, and the like on the basis of the existing house layouts in the house layout library 130. In some embodiments, the computing device 110 may perform the user-type data-related processing based on a trigger or other input by the user 102. Example operations on a house type data basis will be described in more detail in the embodiments below.

In environment 100, computing device 110 may be any type of device having computing capabilities, including a terminal device or a service segment device. The terminal device may be, for example, a mobile terminal, a fixed terminal, or a portable terminal including a mobile handset, a desktop computer, a laptop computer, a notebook computer, a netbook computer, a tablet computer, a media computer, a multimedia tablet, a Personal Communication System (PCS) device, a personal navigation device, a Personal Digital Assistant (PDA), an audio/video player, a digital camera/camcorder, a positioning device, a television receiver, a radio broadcast receiver, an electronic book device, a gaming device, or any combination of the foregoing, including accessories and peripherals of these devices, or any combination thereof. The server devices may include, for example, computing systems/servers, such as mainframes, edge computing nodes, computing devices in a cloud environment, and so forth.

It should be understood that the description of the structure and function of environment 100 is for exemplary purposes only and does not imply any limitation as to the scope of the disclosure.

Generally, the time and economic cost of drawing a house layout is high. Traditionally, for a specific house, it is common to manually measure the relevant data of the house and generate a picture-formatted user-type diagram. Then, performing subsequent operations on the basis of the user-type graph in the picture format is often complicated, and an image processing technology needs to be introduced for implementation. For example, it is determined whether two house type picture contain the same or similar house type by image pixel comparison. Such similarity measures are not only complex and more computationally resource intensive, but may also be less accurate.

According to an embodiment of the present disclosure, an improved house type data processing scheme is proposed. In the scheme, vector diagram data of the house type is constructed and maintained, and the similarity between different house types is measured by utilizing the vector diagram data of the house type. Subsequently, various processing operations for the vector graphics data can be performed based on the similarity of the house types. The particular processing operation may depend on the needs of a particular application.

Since the vector diagram data can represent the attribute information of the house elements in the house type, the similarity of the house type can be determined by directly comparing whether different house types have the same type of house elements and whether the attribute information of the same type of house elements is the same for the vector diagram data. Therefore, on the basis of the vector diagram data of the house type, the similarity of the house type can be measured with lower resource consumption and better accuracy, and the subsequent operation aiming at the vector diagram data is realized based on the similarity. In addition to the measure of similarity, in some embodiments of the present disclosure, vector diagram data of a house type may also be flexibly applied to a variety of house type-related application scenarios.

Some example embodiments of the disclosure will be described below with continued reference to the accompanying drawings.

Fig. 2 illustrates a flow diagram of a process 200 for house type data processing according to some embodiments of the present disclosure. Process 200 may be implemented at computing device 110. For ease of discussion, the process 200 will be described with reference to the environment 100 of FIG. 1.

At block 210, the computing device 110 obtains first vector map data for a first dwelling type and second vector map data for a second dwelling type.

In the embodiments of the present disclosure, it is proposed to construct and maintain vector diagram data of a house type as house type data. The vector diagram data of the house type can indicate attribute information of the house element in the corresponding house type.

Vector graphics, also known as object-oriented images or drawing images. The vector image data may be data of attribute information of the rendering object in the vector file. The vector map data is attribute information for drawing a graphic on the basis of geometric characteristics for defining graphic elements appearing in the vector map. The vector diagram data has the characteristics of small occupied storage space, no distortion of the amplified image and the like. A corresponding vector image may be rendered and presented based on the vector image data.

The graphic elements in the vector image are also referred to as objects. Each object is considered to be an entity having attributes of color, shape, outline, size, location, etc. By defining the relevant information of these properties of the respective object, the corresponding image will be rendered. In a house type scene of a house, an image element or object includes house elements in the house, such as walls, doors, windows, etc. that constitute the house type.

In some embodiments, the vector graphics data may be generated by various tools. The format of the vector map data may include, but is not limited to, ai (illustrator),. bw,. cdr (coreldraw),. dwg,. dxb (drawing exchange binding),. wmf (windows meta format), and the like.

Fig. 3 illustrates a schematic diagram of an example data structure 300 of vector graphics data, in accordance with some embodiments of the present disclosure. In fig. 3, a data structure 300 is used to define a room in a house. FIG. 3 shows definitions of various fields and associated text comments in an example data structure 300. From the data structure 300, Universally Unique Identifiers (UUIDs) of surrounding wall points of a room can be defined and the identities (points) of the various function points located. Further, position information in a room may also be defined, for example, by an offset from an ideal position, and the type (type) of the room, the room number (suffixIndex), the Name (Name), the area (area), whether or not the area (bsrowarea) is displayed, and the like may be defined.

It should be understood that fig. 3 only shows an example data structure for generating vector graphics data for a house type. Other data structures may also be defined depending on the tool generating the vector graphics data and the requirements of the particular application. Embodiments of the present disclosure are not limited in this respect.

In some embodiments, the computing device 110 may maintain a family gallery 130 based on vector graphics data. FIG. 4 illustrates an example of house type data stored in a house type gallery according to some embodiments of the present disclosure. As shown in fig. 4, the house type gallery 130 may store a house type list 410 that includes a plurality of entries, each entry corresponding to a house type.

Specifically, as shown in fig. 4, each entry may include identification information of a house type (referred to as a house type ID), vector diagram data of the house type, and house description information of the house type. This information may be associatively stored in the family gallery 130. In each entry, the house description information may be a simple description about a particular house. In some examples, the house description information may include a house layout of a house, such as X rooms X hall X toilet, etc. In some examples, the house description information may also include house area. In some embodiments, the entries of the house type list 410 may also include location information of the house type, such as cell identification information (referred to as cell ID) as shown in fig. 4. The location information of the house type may additionally or alternatively comprise other information, such as the administrative area where the house is located, etc. In this way, the subscriber type corresponding to a particular geographic area (e.g., a particular cell) may be identified from the subscriber type list 410.

In addition to the family list 410, the family gallery 130 may include other family-related information, such as a family graph list 420, which will be discussed in more detail below.

In the embodiments of the present disclosure, based on the vector diagram data of the house type, various applications for the house type data may be performed, including a measure of the similarity of the house type. The first vector diagram data of the first house type and the second vector diagram data of the second house type, which are to be measured for similarity depending on the application scene, may have different sources.

In some example application scenarios, house-type deduplication of a house-type gallery may be performed. In some examples, when adding a new house type to the house type gallery 130, it may be desirable to determine whether the newly acquired vector graphics data is the same as or similar to the vector graphics data already in the house type gallery 130. In such a scenario, assuming that first vector map data for a first house type is already stored in the house type gallery 130, second vector map data for a second house type may include newly rendered vector map data for a particular house. In other examples, deduplication may be performed on vector graphics data already in the house gallery 130, so both the first vector graphics data and the second vector graphics data may be stored in the house gallery 130.

In some example application scenarios, it may be desirable to perform similar house type searches or similar house type recommendations based on house type similarities, such as finding similar house types from existing house types in the house type gallery 130. In such a scenario, first vector map data for a first house type may be carried in the query request, and second vector map data may be from a query database (e.g., house type gallery 130). The query target is to determine whether the second vector image data can be returned as a query result of the query request. In some embodiments, the query request may be user (e.g., user 102) initiated, or initiated via other events.

At block 220, the computing device 110 determines a house type similarity between the first house type and the second house type by comparing the first vector map data and the second vector map data.

In embodiments of the present disclosure, the house type similarity is measured based on vector diagram data. As described previously, the vector diagram data of the house type can indicate attribute information of the house elements in the corresponding house type. In some embodiments, when comparing vector graphics data, the computing device 110 measures the house type similarity from the large structure of the house type to a specific element. In particular, the computing device 110 may determine, from the first and second vector image data, the respective numbers of rooms of the first and second dwellings, the type of each room, and the types of house elements in the rooms and attribute information for the room elements of each type. The computing device 110 may compare whether the first and second dwelling types have the same number of rooms, such as living and dining rooms, bedrooms, toilets, kitchens, locker rooms, and the like. Then, for rooms of the same type, it is possible to compare whether the numbers of house elements (e.g., walls, doors, and windows, etc.) of respective types within the room are the same, and determine the similarity between attribute information (e.g., the position and size of a wall, the position and size of a door, the position and size of a window, etc.) of the house elements.

By directly comparing vector diagram data, particularly attribute information therein, the similarity of the house types between the two house types can be measured more quickly and accurately. The similarity between the house type of the first house type and the second house type can be expressed in various numerical forms. For example, the house type similarity may be determined as a value in a predetermined continuous value range (such as a range of 0 to 1), or may be one of a plurality of discrete similarity levels. Any other measure of the similarity of the house types is suitable for use herein.

At block 230, the computing device 110 determines a processing operation for at least one of the first vector graphics data and the second vector graphics data based on the house type similarity.

In embodiments of the present disclosure, the processing operations on vector graphics data depend on the specific application scenario. In a house type duplicate removal scenario, one of the first vector graphics data and the second vector graphics data may be discarded from the house type gallery based on the house type similarity.

Fig. 5 illustrates a flow diagram of a vector graphics data based house type deduplication process 500 according to some embodiments of the present disclosure. Process 500 may be implemented at computing device 110.

At block 510, the computing device 110 obtains vector graphics data for the house type. Here, for the sake of discussion, it is assumed that vector map data of the second house type is acquired. The vector graphics data for the second subscriber type may be newly rendered vector graphics data or may be vector graphics data already in the subscriber type gallery 130.

At block 520, the computing device 110 determines whether the house type indicated by the acquired vector graphics data is a duplicate of a house type in the house type gallery 130. Specifically, computing device 110 may compare the vector graphics data for the second house type with the vector graphics data for the house type already stored in house type gallery 130 (e.g., the vector graphics data for the first house type) to determine the house type similarity between the two house types through process 200. The computing device 110 may compare the determined house type similarity to a similarity threshold (also referred to herein as a "first similarity threshold" as used in this scenario) and determine whether the house type is repetitive based on the comparison result. The first similarity threshold can be set according to the value range of the house type similarity and according to the specific application requirements.

In some embodiments, if the house type similarity between the first house type and the second house type is below the first similarity threshold (e.g., equal to or less than the first similarity threshold), the computing device 110 may determine that the obtained second house type is a new house type, which is not duplicated with the house types already in the house type gallery 130. In such a case, at block 530, the computing device 110 may store vector graphics data for the second subscriber type into the subscriber type gallery 130. For example, a new entry may be added to the house type map list 410 of the house type gallery 130 to record the house type ID of the second house type, the second vector map data, the house description information of the second house type, and optionally, also the cell ID of the second house type, and so on.

In some embodiments, if the similarity of the house types between the first house type and the second house type exceeds a first similarity threshold, the computing device 110 may determine that the obtained second house type is the same as or similar to the house type already in the house type gallery 130. At block 540, the computing device 110 may exclude the second vector graphics data from the family gallery 130. In some embodiments, the computing device 110 may need to separately determine whether the existing house type in the house type gallery 130 is similar to the currently acquired second house type until a duplicate house type is found or until all house types in the house type map list 410 of the house type gallery 130 are traversed. In some embodiments, the computing device 110 may store the currently acquired second vector diagram data for the second house type in the house type gallery 130 after all house types stored in the house type gallery 130 have not been found to be duplicate house types.

Through the subscriber pattern deduplication based on the subscriber pattern similarity, a redundancy-free subscriber pattern list, such as a subscriber pattern list within a particular cell or other geographical area, may be maintained. Such a redundancy-free house graph list can also be applied in subsequent applications based on house graphs.

In some embodiments, vector graphics data may be used to support a house-type query. The house type query may be applied, for example, in building a house type for a particular area, such as determining whether the house type does not exist in the house type gallery 130 before drawing the house type to avoid duplicate drawings. The house type query can also be applied in a house type search engine, and the house type is searched by a user browsing a house or used for recommending interesting candidates to the user. In the context of a house type query, it may be determined whether one of the first vector diagram data and the second vector diagram data may be used to determine a query result for the other of the two based on the house type similarity.

Figure 6A illustrates a flow diagram of a vector graphics data based house type query process 600 according to some embodiments of the present disclosure. Process 600 may be implemented at computing device 110.

At block 610, the computing device 110 receives a query request, which may include vector graphics data. Here, for the sake of discussion, it is assumed that vector map data of the second house type is acquired, and the query request in this application scenario is also referred to as a first query request.

At block 620, the computing device 110 looks up the same or similar house type from the house type gallery 130 based on the vector graphics data. Specifically, computing device 110 may compare the vector graphics data for the second house type with the vector graphics data for the house type already stored in house type gallery 130 (e.g., the vector graphics data for the first house type) to determine the house type similarity between the two house types through process 200. The computing device 110 may compare the determined house type similarity to a similarity threshold (also referred to herein as a "second similarity threshold" as used in this scenario) and determine whether the first house type is the same or similar house type of the second house type based on the comparison. The second similarity threshold can be set according to the value range of the house type similarity and according to the specific application requirements. Further, the second similarity threshold may be set to be the same as or different from the first similarity threshold, which is not limited herein.

In some embodiments, the computing device 110 may determine that the first and second tenants in the tenant gallery 130 are similar if the tenant similarity between the first and second tenants exceeds a second similarity threshold. In this case, at block 630 of process 600, the computing device 110 determines a first query result for the first query request based on vector graphics data corresponding to the found same or similar house type (here, "first vector graphics data for the first house type").

In some embodiments, in generating the query result, the computing device 110 may generate a vector house figure for the first house type based on the first vector figure data and determine the first query result based on the example house figure. In other words, the computing device 110 may render the vector graphics data as an image and present the query results in the form of an image. In some embodiments, the computing device 110 may also traverse the user-type graph list 410 in the user-type gallery 130 to determine whether there are additional user types similar to the second user type, thereby expanding the query results. In some embodiments, where house type deduplication has been performed for the house type gallery 130 and the query is targeted to find the same house type, the computing device 110 may stop traversing the house type graph list 410 in the house type gallery 130 after finding the same house type.

In some cases, if the house type similarity between the first house type and the second house type is second below the second similarity threshold, the computing device 110 may determine that the currently found second house type is not a house type similar to the first house type to be queried. In such a case, the computing device 110 may also continue to traverse the family graph list 410 in the family gallery 130 to compare whether the other families in the family gallery 130 are the same as or similar to the first family to be queried. In some embodiments, after traversing the house type gallery 130 and not finding the same or similar house type, the computing device 110 may determine that the first query result of the first query request is empty, i.e., the same or similar house type cannot be found.

In other embodiments of the house type query, if the house type gallery 130 stores house description information for house types, similar house type queries may also be performed based on house description information, as an alternative or in addition to queries using vector graphics data. Figure 6B illustrates a flow diagram of a vector graphics data based house type query process 602 according to some embodiments of the present disclosure. Process 602 may be implemented at computing device 110.

At block 612, the computing device 110 receives a query request, which may include target premises description information. For ease of discussion, the query request in this application scenario is also referred to herein as a second query request.

At block 622, the computing device 110 looks up the same or similar house types from the house type gallery 130 by matching the house description information.

In particular, the computing device 110 may match the target premise description information in the second query request with the premise description information of each entry in the house graph list 410. For example, the target house description information may indicate a house layout to be queried, such as a Y-room Y-toilet or just a Y-room, and/or may indicate a house area to be queried, and so on. The computing device 110 may match different types of premise description information with corresponding types of premise description information in the house graph list 410. Whether the house description information matches may have a predetermined matching criterion. For example, the matching criterion may indicate that some house description information is the same as matching, or all house description information is the same as matching. For example, if the target house-describing information indicates two rooms-one hall and the house-describing information of an entry in the house type map list 410 indicates two rooms-one hall-one toilet, it may also be determined that the target house-describing information matches the house-describing information.

In some embodiments, the query request may also include identification information of the target cell (referred to as the target cell ID). In this way, the computing device 110 may look for matching premise description information for the target premise description information under the entry in the floor plan list 410 having the same cell ID. Therefore, the search range can be reduced, and the query speed is improved.

Upon determining that house-specific information matching the target house-specific information exists in the house-specific gallery 130, the computing device 110 may determine that the house type corresponding to the matched house-specific information is the same or similar house type to be searched. For example, assume that the house type gallery 130 stores at least first vector map data for a first house type. If it is determined that the target house-describing information matches the house-describing information corresponding to the first house type through the matching of the house-describing information, the computing device 110 determines that the first house type is the same or similar house type as the house type to be described by the target house-describing information.

At block 632, the computing device 110 determines a query result (also referred to as a second query result) for the second query request from vector map data corresponding to the located same or similar house type (e.g., first vector map data for the first house type). Based on the vector graphics data, the query result generation here may be similar to the query result generation at block 630 of process 600, and is not described here again.

In some embodiments, based on the target premise description information, computing device 110 may find multiple identical or similar dwellings from the dwelling size gallery 130, and the vector graphics data corresponding to these dwellings may each be used to generate the query result for the second query request in a similar manner.

Many other flexibility applications for the house type data can be provided in addition to the house type deduplication and house type lookup functions based on the house type gallery 130 of the vector diagram data. In general, vector house type maps that are directly rendered based on vector map data are typically in the form of wire-frame maps, presenting house elements in the form of points and lines. In some scenarios, in decoration scenarios, house model design, house renting and selling scenarios, etc., it may be desirable to obtain a house pattern image with a richer visual experience on the basis. In some embodiments, because the vector graphics data can support flexible editing and modification, the user graphics images with different visual styles required in a specific scene can be generated on the basis of the vector graphics data of a certain user.

In particular, computing device 110 may receive target style information indicating a visual style for a particular user type, such as a visual style for a first user type stored in user type gallery 130. The target style information may be determined based on input from the user 102, for example. The target style information may indicate a color style, a texture style, an addition of visual indicia (e.g., text or patterns, etc.), and any other suitable visual style for the first user type.

In response to receiving the target style information, the computing device 110 may retrieve vector graphics data for the indicated user type, e.g., first vector graphics data for a first user type, from the user type gallery 130. Computing device 110 may generate a vector floor plan for the floor plan based on the vector map data. The vector floor plan may be an image consisting of points and lines. For purposes of explanation and not limitation, an example vector floor plan 710 is shown in FIG. 7A. It should be understood that the vector house type graph may also have other presentation forms depending on the way the vector graph data is defined.

Further, computing device 110 may process the vector user-type graph based on the target style information to obtain a corresponding target user-type graph having the visual style indicated by the target style information. Depending on the visual style indicated by the target style information, computing device 110 may add the corresponding visual style to the vector user style diagram through various image processing methods, such as changing colors, adding texture styles, adding desired visual indicia (e.g., room name, area, size of room, furniture appliance graphical elements, etc.), and any other desired visual style. FIG. 7B shows a target user-type diagram 720 with a visual style. It should be understood that fig. 7B is only one specific example, and that a house layout having various other different visual styles may be generated according to the needs of the actual application. Embodiments of the present disclosure are not limited in this respect.

In some embodiments, target floor plans with different visual styles may be generated on the basis of the original vector diagram data or vector floor plan of the floor plan, as desired. In some embodiments, the computing device 110 may also store the generated target user type graph and/or vector user type graph to the user type gallery 130, such as in the user type graph list 420 shown in FIG. 4. In some embodiments, the target house type graph and/or the vector house type graph may be stored in the house type graph list 420 in association with identification information (i.e., a house type ID) of the house type, for example, recorded as one entry of the house type graph list 420.

In some embodiments, the house graph list 420 may be provided for subsequent use, such as repeated application to a certain house graph, or may be applied in a house lookup. Therefore, repeated generation of the floor plan with the same visual style or repeated generation of the vector floor plan can be avoided, and computing resources are saved. As an example, after finding a similar house type from the house type map list 410 based on the vector image data or the house description information, a vector house type map corresponding to the corresponding house type ID and/or a house type map with a certain visual style may be found from the house type map list 420 based on the house type ID of the house type to be provided as the query result. Of course, the family graph list 420 may also be used in other scenarios, and is not limited in this respect.

Fig. 8 shows a schematic block diagram of an apparatus 800 for house type data processing according to some embodiments of the present disclosure. Apparatus 800 may be embodied as or included in terminal device 18. The various modules/components in the apparatus 800 may be implemented by hardware, software, firmware, or any combination thereof.

As shown, the apparatus 800 includes a data acquisition module 810 configured to acquire first vector map data for a first subscriber type and second vector map data for a second subscriber type. The first vector diagram data and the second vector diagram data indicate attribute information of house elements in the first house type and the second house type, respectively. The apparatus 800 further comprises a similarity determination module 820 configured to determine a house type similarity between the first house type and the second house type by comparing the first vector diagram data and the second vector diagram data; and a process determination module 830 configured to determine a processing operation for at least one of the first vector graphics data and the second vector graphics data based on the house type similarity.

In some embodiments, the first vector graphics data is stored in a family gallery. In some embodiments, process determination module 830 includes: a storage module configured to store the second vector diagram data into the family gallery if the family similarity is lower than the first similarity threshold; and an exclusion module configured to exclude the second vector graphics data from the family gallery if the family similarity exceeds a first similarity threshold.

In some embodiments, second vector graphics data is provided with the first query request. In some embodiments, process determination module 830 includes: a first result determination module configured to determine a first query result for the first query request based on the first vector graphics data if the house type similarity exceeds a second similarity threshold; and a query result exclusion module configured to exclude the first vector graphics data from the first query result if the house type similarity is below a second similarity threshold.

In some embodiments, the first result determination module comprises: a first vector house type graph generating module configured to generate a vector house type graph of a first house type based on the first vector graph data; and a genotype-based result determination module configured to determine a first query result based on the vector genotype graph.

In some embodiments, the first vector graphics data is stored in the family gallery in association with identification information of the first family and house description information corresponding to the first family.

In some embodiments, the apparatus 800 further comprises: the query acquisition module is configured to acquire a second query request, and the second query request at least comprises target house description information to be queried; the vector diagram extraction module is configured to extract first vector diagram data from the house type gallery if the target house description information is matched with the house description information corresponding to the first house type; and a second result determination module configured to determine a second query result for the second query request based on the first vector graphics data.

In some embodiments, the apparatus 800 further comprises: an information receiving module configured to receive target style information indicating a visual style for a first user type; the second vector house type graph generating module is configured to generate a vector house type graph of the first house type based on the first vector graph data; and a vector user type graph processing module configured to process the vector user type graph based on the target style information to obtain a target user type graph with a visual style.

In some embodiments, the apparatus 800 further comprises: a haplotype graph storage module configured to store at least one of the target haplotype graph and the vector haplotype graph in association with identification information of the first haplotype to a haplotype graph library.

FIG. 9 illustrates a block diagram that illustrates a computing device 900 in which one or more embodiments of the disclosure may be implemented. It should be understood that the computing device 900 illustrated in FIG. 9 is merely exemplary and should not be construed as limiting in any way the functionality and scope of the embodiments described herein. The computing device 900 shown in fig. 9 may be used to implement the computing device 110 of fig. 1.

As shown in fig. 9, computing device 900 is in the form of a general purpose computing device. Components of computing device 900 may include, but are not limited to, one or more processors or processing units 910, memory 920, storage 930, one or more communication units 940, one or more input devices 950, and one or more output devices 960. The processing unit 910 may be a real or virtual processor and can perform various processes according to programs stored in the memory 920. In a multi-processor system, multiple processing units execute computer-executable instructions in parallel to improve the parallel processing capabilities of computing device 900.

Computing device 900 typically includes a number of computer storage media. Such media may be any available media that is accessible by computing device 900 and includes, but is not limited to, volatile and non-volatile media, removable and non-removable media. The memory 920 may be volatile memory (e.g., registers, cache, Random Access Memory (RAM)), non-volatile memory (e.g., Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory), or some combination thereof. Storage 930 may be a removable or non-removable medium and may include a machine-readable medium, such as a flash drive, a magnetic disk, or any other medium that may be capable of being used to store information and/or data (e.g., training data for training) and that may be accessed within computing device 900.

Computing device 900 may further include additional removable/non-removable, volatile/nonvolatile storage media. Although not shown in FIG. 9, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, non-volatile optical disk may be provided. In these cases, each drive may be connected to a bus (not shown) by one or more data media interfaces. Memory 920 may include a computer program product 925 having one or more program modules configured to perform the various methods or acts of the various embodiments of the disclosure.

The communication unit 940 enables communication with other computing devices over a communication medium. Additionally, the functionality of the components of computing device 900 may be implemented in a single computing cluster or multiple computing machines, which are capable of communicating over a communications connection. Thus, computing device 900 may operate in a networked environment using logical connections to one or more other servers, network Personal Computers (PCs), or another network node.

The input device 950 may be one or more input devices such as a mouse, keyboard, trackball, or the like. Output device 960 may be one or more output devices such as a display, speakers, printer, etc. Computing device 900 may also communicate with one or more external devices (not shown), such as a storage device, a display device, etc., communication devices with one or more devices that enable a user to interact with computing device 900, or communication devices (e.g., network cards, modems, etc.) that enable computing device 900 to communicate with one or more other computing devices, as desired, via communication unit 940. Such communication may be performed via input/output (I/O) interfaces (not shown).

According to an exemplary implementation of the present disclosure, a computer-readable storage medium having stored thereon computer-executable instructions is provided, wherein the computer-executable instructions are executed by a processor to implement the above-described method. According to an exemplary implementation of the present disclosure, there is also provided a computer program product, tangibly stored on a non-transitory computer-readable medium and comprising computer-executable instructions, which are executed by a processor to implement the method described above.

Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus, devices and computer program products implemented in accordance with the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various implementations of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

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

Claims

1. A method of house type data processing, comprising:

acquiring first vector diagram data of a first house type and second vector diagram data of a second house type, wherein the first vector diagram data and the second vector diagram data respectively indicate attribute information of house elements in the first house type and the second house type;

determining a house type similarity between the first house type and the second house type by comparing the first vector diagram data and the second vector diagram data; and

determining a processing operation for at least one of the first vector graphics data and the second vector graphics data based on the house type similarity.

2. The method of claim 1 wherein said first vector graphics data is stored in a family gallery, and wherein determining said processing operation comprises:

if the house type similarity is lower than a first similarity threshold value, storing the second vector diagram data into the house type diagram library; and

and if the house type similarity exceeds the first similarity threshold, excluding the second vector diagram data from the house type gallery.

3. The method of claim 1 wherein said second vector graphics data is provided with a first query request, and wherein determining said processing operation comprises:

determining a first query result for the first query request based on the first vector graphics data if the house type similarity exceeds a second similarity threshold; and

and if the house type similarity is lower than the second similarity threshold, excluding the first vector diagram data from the first query result.

4. The method of claim 3, wherein determining a first query result for the first query request comprises:

generating a vector house type graph of the first house type based on the first vector graph data; and

determining the first query result based on the vector floor plan.

5. The method of claim 1 wherein said first vector graphics data is stored in a family gallery in association with identification information of a first family and premises description information corresponding to said first family.

6. The method of claim 5, further comprising:

acquiring a second query request, wherein the second query request at least comprises target house description information to be queried;

if the target house description information is matched with the house description information corresponding to the first house type, taking out the first vector diagram data from the house type gallery; and

determining a second query result for the second query request based on the first vector graphics data.

7. The method of claim 5, further comprising:

receiving target style information indicating a visual style for the first user type;

processing the vector user type graph based on the target style information to obtain a target user type graph with the visual style.

8. The method of claim 7, further comprising:

storing at least one of the target user type graph and the vector user type graph to a user type gallery in association with identification information of the first user type.

9. An apparatus for house-type data processing, comprising:

a data acquisition module configured to acquire first vector diagram data of a first subscriber type and second vector diagram data of a second subscriber type, the first vector diagram data and the second vector diagram data indicating attribute information of house elements in the first subscriber type and the second subscriber type, respectively;

a similarity determination module configured to determine a house type similarity between the first house type and the second house type by comparing the first vector diagram data and the second vector diagram data; and

a processing determination module configured to determine a processing operation for at least one of the first vector graphics data and the second vector graphics data based on the house type similarity.

10. The apparatus of claim 9, wherein said first vector graphics data is stored in a family gallery, and wherein said processing determination module comprises:

a storage module configured to store the second vector diagram data into the family gallery if the family similarity is lower than a first similarity threshold; and

an exclusion module configured to exclude the second vector graphics data from the family gallery if the family similarity exceeds the first similarity threshold.

11. The apparatus of claim 9 wherein said second vector graphics data is provided with a first query request, and wherein said processing determination module comprises:

a first result determination module configured to determine a first query result for the first query request based on the first vector graphics data if the house type similarity exceeds a second similarity threshold; and

a query result exclusion module configured to exclude the first vector graphics data from the first query result if the house type similarity is below the second similarity threshold.

12. The apparatus of claim 11, wherein the first result determination module comprises:

a first vector house type graph generating module configured to generate a vector house type graph of the first house type based on the first vector graph data; and

a layout-based result determination module configured to determine the first query result based on the vector layout.

13. The apparatus of claim 9 wherein said first vector graphics data is stored in a family gallery in association with identification information of a first family and house description information corresponding to said first family.

14. The device of claim 13, wherein the device further comprises:

the query acquisition module is configured to acquire a second query request, and the second query request at least comprises target house description information to be queried;

a vector diagram extraction module configured to extract the first vector diagram data from the house type gallery if the target house description information matches the house description information corresponding to the first house type; and

a second result determination module configured to determine a second query result for the second query request based on the first vector graphics data.

15. The device of claim 13, wherein the device further comprises:

an information receiving module configured to receive target style information indicating a visual style for the first user type;

a second vector house type graph generating module configured to generate a vector house type graph of the first house type based on the first vector graph data; and

a vector haplotype map processing module configured to process the vector haplotype map based on the target style information to obtain a target haplotype map having the visual style.

16. The device of claim 15, wherein the device further comprises:

a house type graph storage module configured to store at least one of the target house type graph and the vector house type graph in association with identification information of the first house type to a house type graph library.

17. An electronic device, comprising:

at least one processing unit; and

at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions when executed by the at least one processing unit causing the apparatus to perform the method of any of claims 1-8.

18. A computer-readable storage medium, on which a computer program is stored, the computer program being executable by a processor to implement the method according to any one of claims 1 to 8.