CN110147487B - Method and system for determining object heat and processing equipment - Google Patents
Method and system for determining object heat and processing equipment Download PDFInfo
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- CN110147487B CN110147487B CN201710963058.XA CN201710963058A CN110147487B CN 110147487 B CN110147487 B CN 110147487B CN 201710963058 A CN201710963058 A CN 201710963058A CN 110147487 B CN110147487 B CN 110147487B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The application discloses a method, a system and a processing device for determining the heat degree of an object, wherein the method for determining the heat degree of the object comprises the following steps: and normalizing the heat of the objects in the plurality of data sources, de-overlapping the plurality of identical objects to obtain a plurality of de-duplicated residual objects and the heat of the plurality of de-duplicated residual objects after merging the plurality of data sources, and executing sequencing operation on the plurality of de-duplicated residual objects according to the heat. The method and the device can combine the objects of a plurality of data sources in the same category, thereby achieving the purpose of determining the ordered list of all the objects in the data sources in the same category.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method, a system, and a processing device for determining heat of an object.
Background
Currently, there are many data sources that provide objects. Taking a data source as an example of a website, the website may provide many videos or many songs, etc. It will be appreciated that each object corresponds to a heat level that indicates the user's preference. For example, the number of times, frequency, etc. that an object is played may be used to represent how much the user likes the object, i.e., the hotness.
The individual data sources may be an ordered list ordered by the hotness of the object. For example, a music website (data source) may provide songs (objects), one for each song (object), with the music website having an ordered list of the hotness of the individual songs.
In reality, each data source cannot cover all objects due to the limitations of the respective objects (e.g., one music website has the object "none" when it purchases the song "none" copyright, and the other music website does not have the object "none").
Thus, the ordered list in each data source can only indicate the order of the objects that the data source has, and cannot indicate the order of all objects in the same class of data sources. For example, a ordered list of songs for a music website cannot represent the order of all songs in a music category, and a ordered list of videos for a video website cannot represent the order of all videos in a video category.
Thus, there is now a need to determine an ordered list of all objects in the same category of data sources.
Disclosure of Invention
In view of this, the present application provides a method, a system, and a processing device for determining object popularity, which can combine objects of multiple data sources in the same class, so as to achieve the purpose of determining an ordered list of all objects in the same class of data sources.
In order to achieve the above object, the present application provides the following technical features:
a heat calculation system, comprising: a processing device and a plurality of data sources coupled to the processing device;
the processing device is used for normalizing the heat of the objects in the multiple data sources, de-overlapping the multiple identical objects to obtain the heat of the multiple de-duplicated residual objects and the multiple de-duplicated residual objects after the multiple data sources are combined, and executing the sorting operation on the multiple de-duplicated residual objects according to the heat.
Optionally, the processing device is further configured to obtain a sorting result after the sorting operation, and send the sorting result to the plurality of data sources;
the data sources are used for receiving and displaying the sorting results.
A method of determining a heat of an object, comprising:
normalizing the heat of objects in a plurality of data sources;
de-registering the same objects to obtain a plurality of de-duplicated residual objects and the heat of the de-duplicated residual objects after merging the data sources;
and executing sorting operation on the plurality of the residual objects according to the heat.
Optionally, before the normalizing the heat of the objects in the plurality of data sources, the method further includes:
acquiring a plurality of preset attributes of an object in a data source and attribute values of the plurality of preset attributes;
determining a heat attribute for representing heat from a plurality of preset attributes;
and determining the attribute value corresponding to the heat attribute as the original heat value of the object.
Optionally, the determining a heat attribute for representing heat among a plurality of preset attributes includes:
calculating null rates of a plurality of preset attributes in a data source and uniformity of the plurality of preset attributes;
and determining the preset attribute of which the hollow value rate is larger than the first preset value and the uniformity is larger than the second preset value as the heat attribute of the data source.
Optionally, the determining a heat attribute for representing heat among a plurality of preset attributes includes:
calculating null value rates of a plurality of preset attributes in the data source;
and determining the preset attribute of which the hollow value rate in the data source is smaller than the first preset value as the heat attribute of the data source.
Optionally, the de-overlapping the plurality of identical objects to obtain a plurality of de-duplicated remaining objects and a plurality of heat degrees of the de-duplicated remaining objects after merging the plurality of data sources includes:
in the process of merging a plurality of data sources, calculating the similarity among objects in the plurality of data sources, and forming an object set by a plurality of identical objects with the similarity larger than a preset threshold value to obtain a plurality of object sets;
performing de-duplication on each object set, and merging only one de-duplicated residual object reserved by each object set;
a plurality of deduplication residual objects and hotness of the plurality of deduplication residual objects are obtained.
Optionally, the normalizing the heat of the objects in the plurality of data sources includes:
determining a maximum heat value and a minimum heat value among a plurality of data sources;
calculating a first difference value of an original heat value and a minimum heat value of an object, calculating a second difference value of the maximum heat value and the minimum heat value, and taking a quotient of the first difference value and the second difference value as a standard heat value of the object;
and updating the original heat value of the object by using the standard heat value.
Optionally, the method further comprises:
obtaining a sequencing result after sequencing operation;
and respectively sending the sequencing result to a plurality of data sources.
Optionally, the heat comprises: the playing frequency of the object, the playing times of the object, the playing number of the object or the collection times of the object.
A processing apparatus, comprising:
the communication module is used for acquiring the heat of the objects in the plurality of data sources;
and the processor is used for normalizing the heat of the objects in the plurality of data sources, de-overlapping the plurality of identical objects to obtain a plurality of de-duplicated residual objects and the heat of the plurality of de-duplicated residual objects after merging the plurality of data sources, and executing sequencing operation on the plurality of de-duplicated residual objects according to the heat.
Through the technical means, the following beneficial effects can be realized:
the application provides an object heat calculation method, which is characterized in that a plurality of data sources are used for calculating different attributes of object heat, so that the object heat of the plurality of data sources is comparable, and the heat of the plurality of data sources is standardized.
In order to obtain the hotness of all objects in the same class, the application merges objects in multiple data sources (only one object is reserved for multiple identical objects in the merging process, and duplicate objects are deleted), so as to obtain the hotness of multiple duplicate removal residual objects and multiple duplicate removal residual objects. The multiple deduplication remaining objects are all objects in the same class, and the sorting operation can be performed on all object hotness subsequently.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a system for determining heat of an object according to an embodiment of the present disclosure;
FIG. 2 is a flow chart of a method of determining the heat of an object disclosed in an embodiment of the present application;
FIG. 3 is a flow chart of yet another method of determining the heat of an object disclosed in an embodiment of the present application;
FIG. 4 is a flow chart of yet another method of determining the heat of an object disclosed in an embodiment of the present application;
FIG. 5 is a flow chart of yet another method of determining the heat of an object disclosed in an embodiment of the present application;
fig. 6 is a schematic structural diagram of a processing apparatus according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Term interpretation:
data source: the name is meant to be the source of the data, either the device or the original media that provides some desired data.
Heat degree: in this application, the popularity of an object in a data source is expressed as being popular with a user, for example, the number of times the object is played, the frequency, etc. may be used to express the popularity of the object by the user.
Null rate: the number of objects with null data values in a group of object data is the quotient of the number of all objects.
Uniformity: representing the degree of uniformity of the number of objects in each level of an attribute.
To facilitate understanding of the application scenario of the present application by those skilled in the art, the present application provides a heat computing system. Referring to fig. 1, the method specifically includes: a processing device 100 and a plurality of data sources 200 connected to the processing device.
It will be appreciated that it is only practical to order the same category of objects, i.e. to order the videos of the video category, to order the songs of the song category, etc. Multiple data sources in the present application may be sources that provide the same class of objects. Such as a video website that provides video, or a music website that provides songs, etc.
Based on the heat calculation system provided in fig. 1, according to one embodiment of the present application, a method of determining the heat of an object is provided. As shown in fig. 2, the method specifically comprises the following steps:
step S201: the processing device 100 determines the heat of each object in the respective data source.
In order to achieve the purpose of determining all object ordered lists in each data source of the same class, the inventor proposes the following scheme: and merging the objects of the data sources in the same class to obtain the heat of all the objects in the same class. For this purpose, it is first necessary to determine the heat of each object in the respective data source.
According to one embodiment provided herein, referring to fig. 3, the following steps may be included:
step S2011: the processing apparatus 100 acquires object information of a plurality of objects in respective data sources; the object information comprises a plurality of preset attributes and attribute values of the preset attributes.
The processing device 100 may determine a plurality of preset attributes for calculating the heat of the object in advance, for example, the number of plays, the number of players, the number of collections, the number of searches, and the like.
It will be appreciated that each data source may count attribute values for some attributes. The processing device 100 has a data connection with each data source, so that the processing device 100 may obtain, in a crawler manner, an object identifier of each object and attribute values of a plurality of preset attributes of each object from each data source.
The individual data sources may not count the attribute values for each preset attribute set by the processing device. Therefore, when a data source does not count the attribute value of a preset attribute, the attribute values of the preset attributes of all objects in the data source are null values.
The processing device 100 sets a data source identifier for each data source, and after acquiring a plurality of object information in each data source, stores the plurality of object information of each data source in correspondence with each data source identifier.
Referring to table 1, examples of a plurality of object information of respective data sources are stored for the processing apparatus 100.
TABLE 1
Optionally, the processing device 100 may perform data cleansing on the plurality of object information of each data source to ensure rationalization of the plurality of object information in each data source. Cleaning the data may include:
first, the abnormal attribute value is deleted. Some attribute values in each data source may be abnormal values, so that whether each attribute value is within a preset reasonable range is judged, and if the abnormal attribute value is not deleted.
Second, the data format of the attribute values is standardized. Because the data formats of the data sources are not uniform, the data formats of the attribute values can be uniform for facilitating subsequent processing.
Third, redundant data values are deleted. Some data sources may backup data in order to protect the data. The present embodiment deletes the redundant data value.
It will be appreciated that the object information of each data source may be cleaned, and other content may be included, which is not explicitly recited herein.
Step S2012: the processing device 100 determines a heat attribute for each data source among a plurality of preset attributes, respectively.
Each data source originally has an attribute for calculating the object heat, some are the heat attribute with the number of plays as the object heat, some are the heat attribute with the number of players as the object heat, some are the heat attribute with the number of collections as the object heat, and so on.
Thus, the processing device 100 may re-determine the heat attribute for each data source so that the indicators of the heat attribute determined by each data source are uniform (indicators are uniform, but the heat attributes used to determine heat may be different).
The present application provides two indicators of determining heat attributes:
a first index: preset attributes with lowest null rate.
Taking a preset attribute of a data source as an example, the processing device 100 counts the number of objects in the preset attribute of the data source, which do not have a data value (null value), and the number of all objects in the data source, calculates the quotient of the two objects, and determines the quotient as the null value rate of the preset attribute.
The lower the null rate of a preset attribute, the greater the number of objects having attribute values in the preset attribute. Calculating object hotness using the preset attribute may calculate object hotness of more objects.
The second index: the attribute with highest uniformity.
Taking a preset attribute of a data source as an example, the processing device 100 sets several levels between the minimum and maximum values of each preset attribute. The processing device 100 may count the number of objects whose attribute values are at each level, respectively.
The more the number of objects in each level tends to be the same, the higher the uniformity.
In this step, the processing device 100 may calculate the null rate of each preset attribute and the uniformity of each preset attribute in each data source; and then, determining the preset attribute with the hollow value rate larger than the first preset value and the uniformity larger than the second preset value of each data source as the heat attribute of each data source.
The first preset value and the second preset value are preset data values respectively, and specific data values can be specifically determined according to actual situations and are not limited herein.
Step S2013: and determining the heat value corresponding to the heat attribute of each object in each data source as the heat of each object.
Returning to fig. 2, the process advances to step S202: the processing device 100 normalizes the heat of objects in the plurality of data sources. The method comprises the steps of respectively normalizing the heat of each object in each data source to obtain a standard heat value, and updating the original heat value of the object by using the standard heat value of the object.
Since the object information in each data source is not the same, the heat attribute for calculating heat determined based on the same index is not the same. Some data sources use the number of plays as the heat attribute, some data sources use the frequency of plays as the heat attribute, etc.
The object hotness of the respective data sources is not comparable because of the non-uniformity of the attributes used to calculate the object hotness in the respective data sources. Thus, the object hotness of the individual data sources can be standardized.
The embodiment can use dispersion normalization to normalize the object heat of each data source. Referring to fig. 4, a specific process may include:
step S2021: a maximum heat value and a minimum heat value are determined in each data source.
And ordering the heat of each object in all objects contained in each data source to obtain a maximum heat value and a minimum heat value.
Step S2022: calculating a first difference value of an original heat value and a minimum heat value of an object, calculating a second difference value of the maximum heat value and the minimum heat value, and taking the quotient of the first difference value and the second difference value as a standard heat value of the object.
Step S2023: and updating the original heat value of the object by using the standard heat value.
The present embodiment provides a way of data normalization, and it will be appreciated that there are also a variety of ways of data normalization, such as: such as extremum, standard deviation, tri-fold, semi-normal distribution, etc., are not explicitly recited herein. The specific implementation of data normalization is already a mature technology and will not be described in detail here.
Returning next to fig. 2, step S203 is entered: and de-registering the plurality of identical objects to obtain a plurality of de-duplicated residual objects and the heat of the plurality of de-duplicated residual objects after merging the plurality of data sources.
After normalizing the hotness of each object in each data source, the objects of each data source may be merged. Since one object may exist in multiple data sources (e.g., multiple music websites each containing the same song), it is necessary to encounter situations where multiple data sources contain the same object.
According to one embodiment of the present application, referring to fig. 5, the implementation of this step includes:
step S2031: in the process of merging the plurality of data sources, calculating the similarity among the objects in the plurality of data sources, and forming an object set by a plurality of identical objects with the similarity larger than a preset threshold value to obtain a plurality of object sets.
The object information includes an index of object similarity, and may include: program introduction, creator, authoring company, date of release, region, language, etc. For one object of one data source, the similarity of the object with each object in the other data sources is calculated based on the similarity index.
And then, determining a plurality of objects with the similarity with the object larger than the preset similarity in other data sources as the same object with the object. The identical objects in the various data sources may form an object set that includes a plurality of identical objects.
It is understood that objects outside the set of objects are objects in the respective data sources that do not have the same object.
Step S2032: and carrying out de-duplication on each object set, and merging only one de-duplicated residual object reserved by each object set.
Since the object set includes a plurality of identical objects, the objects are identical but the objects are not hot enough. Therefore, the warmth of the same object can be unified.
The way to unify the warmth of the same objects may include: the maximum value of the object concentrated heat is determined as the unified object heat, or the average value of the object concentrated heat is determined as the unified object heat, and so on.
For each object set, deduplicating the object set retains only one object to delete redundant objects. The objects reserved in the object set are called deduplication residual objects, and the hotness value of the deduplication residual objects is a unified post-hotness value.
Step S2033: a plurality of deduplication residual objects and hotness of the plurality of deduplication residual objects are obtained.
In the process of merging a plurality of data sources, after the deduplication operation is performed on the object sets, merging only one deduplication residual object reserved by each object set to obtain all objects in the same class of data sources.
Returning next to fig. 2, step S204 is entered: the processing device 100 performs a sorting operation on the plurality of deduplicated remaining objects according to the hotness.
Step S205: the processing device 100 obtains the sort result after performing the sort operation and transmits the sort result to the plurality of data sources.
Step S206: multiple sources of data 200 receive and display the ranking results.
From the above, it can be known that the beneficial effects of the present application are as follows:
the application provides an object heat calculation method, which is characterized in that a plurality of data sources are used for calculating different attributes of object heat, so that the object heat of the plurality of data sources is comparable, and the heat of the plurality of data sources is standardized.
In order to obtain the hotness of all objects in the same class, the application merges objects in multiple data sources (only one object is reserved for multiple identical objects in the merging process, and duplicate objects are deleted), so as to obtain the hotness of multiple duplicate removal residual objects and multiple duplicate removal residual objects. The multiple deduplication remaining objects are all objects in the same class, and the sorting operation can be performed on all object hotness subsequently. Referring to fig. 6, the present application further provides a processing apparatus, including:
the communication module is used for acquiring the heat of a plurality of objects in each data source;
and the processor is used for normalizing the heat of the objects in the plurality of data sources, de-overlapping the plurality of identical objects to obtain a plurality of de-duplicated residual objects and the heat of the plurality of de-duplicated residual objects after merging the plurality of data sources, and executing sequencing operation on the plurality of de-duplicated residual objects according to the heat.
The functions described in the method of this embodiment, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computing device readable storage medium. Based on such understanding, a portion of the embodiments of the present application that contributes to the prior art or a portion of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computing device (which may be a personal computer, a server, a mobile computing device or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, randomAccess Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, so that the same or similar parts between the embodiments are referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A heat calculation system, comprising: a processing device and a plurality of data sources coupled to the processing device;
the processing equipment is used for normalizing the heat of the objects in the plurality of data sources, de-overlapping the plurality of same objects to obtain a plurality of de-duplicated residual objects and the heat of the plurality of de-duplicated residual objects after the plurality of data sources are combined, and executing sequencing operation on the plurality of de-duplicated residual objects according to the heat;
the de-overlapping the same objects to obtain a plurality of de-duplicated residual objects and a plurality of heat degrees of the de-duplicated residual objects after merging the data sources, including:
in the process of merging a plurality of data sources, calculating the similarity among objects in the plurality of data sources, and forming an object set by a plurality of identical objects with the similarity larger than a preset threshold value to obtain a plurality of object sets;
performing de-duplication on each object set, and merging only one de-duplicated residual object reserved by each object set;
obtaining the heat of a plurality of residual objects after the duplication elimination and a plurality of residual objects after the duplication elimination; the plurality of deduplication remaining objects are all objects in the same class.
2. The system of claim 1, wherein,
the processing equipment is further used for obtaining the sequencing result after the sequencing operation and sending the sequencing result to the plurality of data sources;
the data sources are used for receiving and displaying the sorting results.
3. A method of determining the heat of an object, comprising:
normalizing the heat of objects in a plurality of data sources;
de-registering the same objects to obtain a plurality of de-duplicated residual objects and the heat of the de-duplicated residual objects after merging the data sources;
performing sorting operation on the plurality of deduplication residual objects according to the heat;
the de-overlapping the same objects to obtain a plurality of de-duplicated residual objects and a plurality of heat degrees of the de-duplicated residual objects after merging the data sources, including:
in the process of merging a plurality of data sources, calculating the similarity among objects in the plurality of data sources, and forming an object set by a plurality of identical objects with the similarity larger than a preset threshold value to obtain a plurality of object sets;
performing de-duplication on each object set, and merging only one de-duplicated residual object reserved by each object set;
obtaining the heat of a plurality of residual objects after the duplication elimination and a plurality of residual objects after the duplication elimination; the plurality of deduplication remaining objects are all objects in the same class.
4. The method of claim 3, further comprising, prior to said normalizing the heat of objects in the plurality of data sources:
acquiring a plurality of preset attributes of an object in a data source and attribute values of the plurality of preset attributes;
determining a heat attribute for representing heat from a plurality of preset attributes;
and determining the attribute value corresponding to the heat attribute as the original heat value of the object.
5. The method of claim 4, wherein determining a heat attribute for representing heat among a plurality of preset attributes comprises:
calculating null rates of a plurality of preset attributes in a data source and uniformity of the plurality of preset attributes;
and determining the preset attribute of which the hollow value rate is larger than the first preset value and the uniformity is larger than the second preset value as the heat attribute of the data source.
6. The method of claim 4, wherein determining a heat attribute for representing heat among a plurality of preset attributes comprises:
calculating null value rates of a plurality of preset attributes in the data source;
and determining the preset attribute of which the hollow value rate in the data source is smaller than the first preset value as the heat attribute of the data source.
7. The method of claim 3, wherein normalizing the heat of objects in the plurality of data sources comprises:
determining a maximum heat value and a minimum heat value among a plurality of data sources;
calculating a first difference value of an original heat value and a minimum heat value of an object, calculating a second difference value of the maximum heat value and the minimum heat value, and taking a quotient of the first difference value and the second difference value as a standard heat value of the object;
and updating the original heat value of the object by using the standard heat value.
8. A method as recited in claim 3, further comprising:
obtaining a sequencing result after sequencing operation;
and respectively sending the sequencing result to a plurality of data sources.
9. A method according to claim 3, wherein the heating comprises:
the playing frequency of the object, the playing times of the object, the playing number of the object or the collection times of the object.
10. A processing apparatus, comprising:
the communication module is used for acquiring the heat of the objects in the plurality of data sources;
the processor is used for normalizing the heat of the objects in the plurality of data sources, de-overlapping the plurality of identical objects to obtain a plurality of de-duplicated residual objects and the heat of the plurality of de-duplicated residual objects after the plurality of data sources are combined, and executing sequencing operation on the plurality of de-duplicated residual objects according to the heat;
the de-overlapping the same objects to obtain a plurality of de-duplicated residual objects and a plurality of heat degrees of the de-duplicated residual objects after merging the data sources, including:
in the process of merging a plurality of data sources, calculating the similarity among objects in the plurality of data sources, and forming an object set by a plurality of identical objects with the similarity larger than a preset threshold value to obtain a plurality of object sets;
performing de-duplication on each object set, and merging only one de-duplicated residual object reserved by each object set;
obtaining the heat of a plurality of residual objects after the duplication elimination and a plurality of residual objects after the duplication elimination; the plurality of deduplication remaining objects are all objects in the same class.
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