CN109344247B - Method and apparatus for outputting information - Google Patents
Method and apparatus for outputting information Download PDFInfo
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- CN109344247B CN109344247B CN201811146123.0A CN201811146123A CN109344247B CN 109344247 B CN109344247 B CN 109344247B CN 201811146123 A CN201811146123 A CN 201811146123A CN 109344247 B CN109344247 B CN 109344247B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
- G06F40/216—Parsing using statistical methods
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
Abstract
The embodiment of the application discloses a method and a device for outputting information. One embodiment of the method comprises: acquiring track information of a first condition of at least one path for a predetermined number of days and track information of a second condition for a predetermined number of days; for a path in at least one path, generating a second condition track characteristic of the path and a first condition track characteristic of the path according to track information of a second condition of the path in a preset number of days and track information of a first condition of the path in a preset number of days respectively; for a path in at least one path, determining a similarity between a second conditional trajectory feature of the path and a first conditional trajectory feature of the path; a first predetermined number of paths are selected based on the similarity, and path names of the selected paths are output. The embodiment can predict the traffic jam road section caused by the water accumulation in the first condition, so that the navigation route is optimized.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to a method and a device for outputting information.
Background
In the traffic operation condition of urban road network, severe weather is an important influence factor. For example, road ponding, haze and snowfall caused by heavy rainfall and unsmooth drainage can cause the traffic flow operation to be seriously influenced. When the road water depth reaches a certain degree, the road traffic flow is completely interrupted, so that a large number of upstream vehicles are gathered, and the running speed of a motorcade approaches zero. With the lapse of time, the congestion phenomenon will spread from the accumulated water section to the upstream road section and the upper crossing road section continuously, thereby causing traffic congestion in a certain range and affecting the operation condition of the whole road network. In addition, traffic control performed for reasons such as meetings also affects the overall operating conditions of the road network.
The congestion information used in the navigation process is usually collected by a specially assigned person after field investigation. The congestion road section information can also be fed back by traffic management and users, but the feedback information is limited in quantity and poor in real-time performance, and in addition, the confidence level of the congestion road section reflected by the users is difficult to guarantee. In addition, the congested link information provided by map providers is typically static and not updated in real-time.
Disclosure of Invention
The embodiment of the application provides a method and a device for outputting information.
In a first aspect, an embodiment of the present application provides a method for outputting information, including: acquiring track information of a first condition of at least one path for a predetermined number of days and track information of a second condition for a predetermined number of days; for a path in at least one path, generating a second condition track characteristic of the path and a first condition track characteristic of the path according to track information of a second condition of the path in a preset number of days and track information of a first condition of the path in a preset number of days respectively; for a path in at least one path, determining a similarity between a second conditional trajectory feature of the path and a first conditional trajectory feature of the path; a first predetermined number of paths are selected based on the similarity, and path names of the selected paths are output.
In some embodiments, selecting a first predetermined number of paths based on the similarity includes: determining a first similarity between the second conditional track quantity feature of the path and the first conditional track quantity feature of the path; determining a second similarity between the second conditional trajectory speed feature of the path and the first conditional trajectory speed feature of the path; determining a weighted sum of the first similarity and the second similarity as a first score for the path, wherein the first score is inversely related to the similarity; and selecting a first preset number of paths from at least one path according to the sequence of the first score from high to low.
In some embodiments, the trajectory information includes a number of trajectories and a trajectory speed; and generating a second condition track characteristic of the path and a first condition track characteristic of the path according to the track information of the second condition of the path in the preset days and the track information of the first condition of the path in the preset days respectively, wherein the method comprises the following steps: generating a second condition track quantity characteristic of the path and a second condition track speed characteristic of the path according to the track quantity and the track speed in the track information of the second condition of the preset days of the path respectively; acquiring rainfall of each first condition in the first conditions of the preset days; and dividing the track quantity and the track speed in the track information of the first condition of the preset days of the path by the rainfall of the corresponding first condition to generate a first condition track quantity characteristic of the path and a first condition track speed characteristic of the path.
In some embodiments, the method further comprises: determining the difference between the maximum value and the minimum value of the track speed in the track information of the first condition of the preset days as a first condition gap coefficient; determining the difference between the maximum value and the minimum value of the track speed in the track information of the second condition of the preset days as a second condition difference coefficient; updating the first conditional track speed characteristic of the path to be the product of the first conditional track speed characteristic of the path and the first condition difference coefficient; the second conditional trajectory speed characteristic of the path is updated to be the product of the second conditional trajectory speed characteristic of the path and a second condition difference coefficient.
In some embodiments, the method further comprises: acquiring at least one piece of information with the date in a preset time range; for information in at least one piece of information, determining the score of the information based on the word frequency of a preset keyword set in the information; for the path in the selected first preset number of paths, matching the path name of the path with at least one piece of information, determining the information with the highest matching degree with the path name, and determining the score of the information with the highest matching degree with the path name as the second score of the path; and selecting a second preset number of paths from the selected first preset number of paths according to the sequence of the sum of the first score and the second score from large to small, and outputting the path names of the selected second preset number of paths.
In some embodiments, matching the path name of the path with at least one piece of information includes: selecting at least one information message with a score higher than a predetermined threshold value from the at least one information message as at least one candidate information message; and for the path in the selected first predetermined number of paths, matching the path name of the path with at least one piece of candidate information.
In some embodiments, determining the score of the information based on the word frequency of the predetermined keyword set in the information comprises: for the keywords in a preset keyword set, determining the word frequency reverse file frequency of the keywords in the information; determining the sum of the word frequency reverse document frequency of each keyword as the weight characteristic in the information; determining the number of types of keywords appearing in the information as diversity characteristics in the information; determining the weighted sum of the weight characteristic and the diversity characteristic as the score of the information.
In a second aspect, an embodiment of the present application provides an apparatus for outputting information, including: an acquisition unit configured to acquire trajectory information of a first condition for a predetermined number of days and trajectory information of a second condition for a predetermined number of days of at least one route; the generating unit is configured to generate a second condition track characteristic of the path and a first condition track characteristic of the path according to track information of a second condition of the path in a preset number of days and track information of a first condition of the path in a preset number of days respectively for the path in at least one path; a determining unit configured to determine, for a path of at least one path, a similarity between a second conditional trajectory feature of the path and a first conditional trajectory feature of the path; a selecting unit configured to select a first predetermined number of paths based on the similarity, and output path names of the selected paths.
In some embodiments, the selection unit is further configured to: determining a first similarity between the second conditional track quantity feature of the path and the first conditional track quantity feature of the path; determining a second similarity between the second conditional trajectory speed feature of the path and the first conditional trajectory speed feature of the path; determining a weighted sum of the first similarity and the second similarity as a first score for the path, wherein the first score is inversely related to the similarity; and selecting a first preset number of paths from at least one path according to the sequence of the first score from high to low.
In some embodiments, the trajectory information includes a number of trajectories and a trajectory speed; and the generating unit is further configured to: generating a second condition track quantity characteristic of the path and a second condition track speed characteristic of the path according to the track quantity and the track speed in the track information of the second condition of the preset days of the path respectively; acquiring rainfall of each first condition in the first conditions of the preset days; and dividing the track quantity and the track speed in the track information of the first condition of the preset days of the path by the rainfall of the corresponding first condition to generate a first condition track quantity characteristic of the path and a first condition track speed characteristic of the path.
In some embodiments, the apparatus further comprises a correction unit configured to: determining the difference between the maximum value and the minimum value of the track speed in the track information of the first condition of the preset days as a first condition gap coefficient; determining the difference between the maximum value and the minimum value of the track speed in the track information of the second condition of the preset days as a second condition difference coefficient; updating the first conditional track speed characteristic of the path to be the product of the first conditional track speed characteristic of the path and the first condition difference coefficient; the second conditional trajectory speed characteristic of the path is updated to be the product of the second conditional trajectory speed characteristic of the path and a second condition difference coefficient.
In some embodiments, the apparatus further comprises a filtering unit configured to: acquiring at least one piece of information with the date in a preset time range; for information in at least one piece of information, determining the score of the information based on the word frequency of a preset keyword set in the information; for the path in the selected first preset number of paths, matching the path name of the path with at least one piece of information, determining the information with the highest matching degree with the path name, and determining the score of the information with the highest matching degree with the path name as the second score of the path; and selecting a second preset number of paths from the selected first preset number of paths according to the sequence of the sum of the first score and the second score from large to small, and outputting the path names of the selected second preset number of paths.
In some embodiments, the filtration unit is further configured to: selecting at least one information message with a score higher than a predetermined threshold value from the at least one information message as at least one candidate information message; and for the path in the selected first predetermined number of paths, matching the path name of the path with at least one piece of candidate information.
In some embodiments, the filtration unit is further configured to: for the keywords in a preset keyword set, determining the word frequency reverse file frequency of the keywords in the information; determining the sum of the word frequency reverse document frequency of each keyword as the weight characteristic in the information; determining the number of types of keywords appearing in the information as diversity characteristics in the information; determining the weighted sum of the weight characteristic and the diversity characteristic as the score of the information.
In a third aspect, an embodiment of the present application provides an electronic device, including: one or more processors; a storage device having one or more programs stored thereon which, when executed by one or more processors, cause the one or more processors to implement a method as in any one of the first aspects.
In a fourth aspect, the present application provides a computer readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method according to any one of the first aspect.
According to the method and the device for outputting the information, the track characteristics of the first condition and the second condition of the multiple paths are compared, and the path with the large track difference is selected as the water accumulation point. Therefore, the efficiency and the real-time performance of finding accumulated water points in the traffic road are improved, and the labor cost is reduced.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture diagram in which one embodiment of the present application may be applied;
FIG. 2 is a flow diagram for one embodiment of a method for outputting information, in accordance with the present application;
FIGS. 3a, 3b are schematic diagrams of an application scenario of a method for outputting information according to the present application;
FIG. 4 is a flow diagram of yet another embodiment of a method for outputting information according to the present application;
FIG. 5 is a schematic block diagram illustrating one embodiment of an apparatus for outputting information according to the present application;
FIG. 6 is a schematic block diagram of a computer system suitable for use in implementing an electronic device according to embodiments of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 shows an exemplary system architecture 100 to which embodiments of the present method for outputting information or apparatus for outputting information may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium of communication paths between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication paths, or fiber optic cables, among others.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have various communication client applications installed thereon, such as navigation applications, web browser applications, shopping applications, search applications, instant messaging tools, mailbox clients, social platform software, and the like.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices with information collecting function, including but not limited to a smartphone, a tablet computer, a monitoring probe on road side, etc. which is held by a pedestrian or mounted on a vehicle. The monitoring probe can acquire the speed and the times of pedestrians or vehicles passing through the road and then report the speed and the times to the server. The intelligent mobile phone or the tablet personal computer which is held by the pedestrian or carried by the vehicle can also report the information of the current speed, the passing path and the like collected by the navigation application to the server, and the server counts the average speed and the total frequency of the people or the vehicles passing through each path. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the electronic apparatuses listed above. It may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services) or as a single piece of software or software module. And is not particularly limited herein.
The server 105 may be a server that provides various services, such as a background map server that provides support for maps displayed on the terminal devices 101, 102, 103. The background map server may analyze and otherwise process data such as the received map request, and feed back a processing result (for example, map data including the waterlogging point) to the terminal device.
The server may be hardware or software. When the server is hardware, it may be implemented as a distributed server cluster formed by multiple servers, or may be implemented as a single server. When the server is software, it may be implemented as multiple pieces of software or software modules (e.g., multiple pieces of software or software modules used to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.
It should be noted that the method for outputting information provided in the embodiment of the present application is generally performed by the server 105, and accordingly, the apparatus for outputting information is generally disposed in the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of a method for outputting information in accordance with the present application is shown. The method for outputting information comprises the following steps:
In this embodiment, an execution subject (e.g., the server shown in fig. 1) of the method for outputting information may acquire the historical trajectory information of at least one path from a third-party server through a wired connection manner or a wireless connection manner. The execution body may also acquire navigation information of the terminal from a terminal for navigation that is mounted on a vehicle or a terminal for navigation that is personal and then count track information. The executive body can also acquire track information from the traffic monitoring camera. The path refers to an urban road, and particularly refers to a road section which can generate accumulated water. The history track information refers to track information of the first condition for a predetermined number of days and track information of the second condition for a predetermined number of days. The predetermined number of days may be consecutive or non-consecutive days, such as 5 days, 10 days, etc. The first condition refers to a condition affecting traffic to be predicted, for example, traffic control, weather conditions are rain, haze, and the like. The second condition refers to a day of ideal traffic conditions, for example, a day with no traffic control, precipitation of 0, and excellent air quality, which may be a sunny day. The trajectory information may include trajectory speed and number of trajectories. Where the number of tracks refers to the sum of the frequency of people or cars passing the path during the day. If a vehicle passes the path 10 times, it is calculated 10 times. The trajectory speed may include an average of the speeds of persons or vehicles passing through the path during the day and may also include a maximum and minimum of the speed during the day.
In this embodiment, the historical track information is processed to establish a track-to-track index, and the attribute value of each track is composed of two parts, namely the track number and the average speed of the people or vehicles passing through the track. Let path be l, number of tracks t, average velocity v, select second/first condition number n, s represents second condition, r represents first condition. The trajectory characteristics may include a number of trajectories characteristic and/or a trajectory speed characteristic. Trace quantity feature t of second conditionsMay be the frequency of the track, i.e.Wherein
Is the number of the trajectories of the nth second condition through the path l, the trajectory speed characteristic v of the second conditionsMay be the average speed through the path, i.e.
Is the average speed of the nth second condition through path i. Trace quantity feature t of first conditionrAnd the trajectory velocity characteristic vrAre respectively as
Is the number of traces of the nth second condition through path i,
is the average speed of the nth second condition through path i.
In some optional implementations of this embodiment, whether the path is considered different in precipitation amount for the first condition is determinedThe contribution rate of the water accumulation points should be different, for example, the first condition with larger precipitation amount should be different from the second condition, i.e. the number of tracks and the average speed of the first condition should be smaller. Assuming that the second conditional precipitation is 0 and the first conditional precipitation is m ═ m1，m2，...，mn]Wherein m represents the amount of precipitation per day for n days, and mnRepresents the amount of precipitation on day n. The trace quantity characteristic t of the first conditionrAnd the trajectory velocity characteristic vrComprises the following steps:
in some optional implementations of this embodiment, the method further includes: 1. and determining the difference between the maximum value and the minimum value of the track speed in the track information of the first condition of the preset days as a first condition gap coefficient. The first condition gap coefficient is a vector and is composed of the maximum value and the minimum value of the track speed of each first condition. 2. And determining the difference between the maximum value and the minimum value of the track speed in the track information of the second condition of the preset days as a second condition difference coefficient. Wherein the second condition gap coefficient is a vector composed of a maximum value and a minimum value of the trajectory speed for each second condition. 3. The first conditional track speed characteristic of the path is updated to be the product of the first conditional track speed characteristic of the path and the first condition difference coefficient. 4. The second conditional trajectory speed characteristic of the path is updated to be the product of the second conditional trajectory speed characteristic of the path and a second condition difference coefficient.
Considering that pedestrians mostly travel at a slow speed due to wet and slippery roads in the first condition, the difference between the maximum value and the minimum value of the track speed is small, and the difference between the second condition and the track speed is large. Assuming that the maximum value of the second conditional track speed is
Therein, maxsThe maximum value of each second conditional trajectory speed is indicated.
The maximum value of the nth second condition trajectory speed is indicated. The minimum value of each second condition speed is
Represents the minimum value of the nth second condition trajectory speed. Each first conditional speed having a maximum value of
Representing the maximum value of the nth first conditional track speed. The minimum value of the speed of each first condition is
Representing the minimum value of the nth first conditional trajectory speed. The second condition difference coefficient is (max)s-mins) The first condition gap coefficient is (max)r-minr). Trajectory speed characteristic v of second conditionsFirst condition trajectory velocity feature vrRespectively as follows:
vs＝vs⊙(maxs-mins)
vr＝vr⊙(maxr-minr)
In this embodiment, for a path of at least one path, a first similarity between a second conditional track quantity feature of the path and a first conditional track quantity feature of the path may be determined. Or determining a second similarity between the second conditional trajectory speed characteristic of the path and the first conditional trajectory speed characteristic of the path. The first similarity and the second similarity can also be weighted and summed to serve as the similarity of the path.
In this embodiment, a first predetermined number of paths may be selected from the plurality of paths in order of increasing similarity, and the path names of the selected paths may be output. A similarity threshold may also be set, and when the similarity is smaller than the similarity threshold, it indicates that the path has a large difference between the second condition and the first condition, and the possibility of becoming a water accumulation point is very high in the first condition. A path may therefore be selected from the plurality of paths for which the similarity between the trajectory speed feature of the first condition and the trajectory speed feature of the second condition is less than the similarity threshold. A path may also be selected from the plurality of paths where a similarity between the number of tracks feature for the first condition and the number of tracks feature for the second condition is less than a similarity threshold. A path from the plurality of paths may also be selected for which a weighted sum of a first similarity and a second similarity between the first condition and the second condition is less than a similarity threshold. The path name can be directly output, and the path name can also be marked in a navigation map, so that the user can conveniently download and use the path name. Therefore, the user is guided to avoid the accumulated water path, so that congestion can be prevented, and the safety of vehicles and people can be guaranteed.
In some optional implementations of this embodiment, selecting the first predetermined number of paths based on the similarity includes:
step 2041, a first similarity between the second conditional track quantity feature of the path and the first conditional track quantity feature of the path is determined.
The first similarity S1 may be characterized using cosine similarity. Is represented by the following formula, wherein tsTrace quantity characteristic of a second condition for a path, trTrack quantity feature for a first condition of a path:
step 2042, determine a second similarity between the second conditional trajectory speed feature of the path and the first conditional trajectory speed feature of the path.
The second similarity S2 may be characterized using cosine similarity. Is represented by the following formula, wherein vsA trajectory speed characteristic of a second condition of the path, vrTrajectory speed feature for a first condition of the path:
step 2043 determines a weighted sum of the first similarity and the second similarity as the first score for the path.
First score of each path scorelIs defined as:
as can be seen from the above equation, the scoring function is composed of two parts, the first part is the difference degree of the number of tracks of the second/first condition through each path, wherein the difference is measured by the negative cosine similarity. The second component is the difference in average velocity through each path. In addition, both α and β are hyper-parameters that are used to balance the second/first condition through the track number score and the track speed score, where track speed refers to average speed. Where α represents the weight of the track number score and β represents the weight of the track velocity score. And after the score of each path is calculated, selecting the path with the highest score as a water accumulation point. Wherein the first score is inversely related to the similarity. That is, the higher the similarity, the lower the score, and the less likely it is a water spot.
Step 2044, a first predetermined number of paths are selected from the at least one path according to the descending order of the first score.
Since the first score is inversely related to the similarity. That is, the higher the similarity, the lower the score, and the less likely it is a water spot. Therefore, the method is equivalent to selecting a first preset number of paths from at least one path in the sequence of similarity from low to high.
With continuing reference to fig. 3a, 3b, fig. 3a, 3b are schematic diagrams of application scenarios of the method for outputting information according to the present embodiment. In the application scenario of fig. 3a, the server obtains track information of 5 sunny days and track information of 5 first conditions of multiple paths from the monitoring system of the traffic administration office. Wherein, the track information packet comprises track speed and track number. The trajectory features generated from the trajectory information may then be corrected based on the amount of rainfall. The trajectory features include a trajectory speed feature and a trajectory number feature. And calculating the similarity between the track speed characteristics of all paths on a sunny day and the track speed characteristics of the first condition and the similarity between the track quantity characteristics of all paths on a sunny day and the track quantity characteristics of the first condition. For each path, the weighted sum of the two similarities is the first score for that path. Filtering out paths with low first scores to obtain a first preset number of paths. Fig. 3b shows a map of the path obtained by the method of the present application, which is a water spot distribution map.
With further reference to fig. 4, a flow 400 of yet another embodiment of a method for outputting information is shown. The process 400 of the method for outputting information includes the steps of:
In step 403, for a path in at least one path, determining a similarity between a second conditional trajectory feature of the path and a first conditional trajectory feature of the path.
The steps 401 and 404 are substantially the same as the steps 201 and 204, and therefore, the description thereof is omitted.
In this embodiment, the information may be news, microblog, etc. capable of reflecting the actual hot spot. The predetermined time refers to a date or a period of time before or a period of time after the track information of the first condition acquired in step 201 corresponds to. For example, if the first condition is 2018, month 8, the predetermined time may be 2018, month 8 or within 3 days thereafter. It may also be number 8/7 of 2018. Since the information may be weather forecast information.
In this embodiment, a keyword set may be preset, and the keyword set of the phase may be selected when prediction is performed for different conditions. For predicting a rainfall-induced congested road section, the keyword set may include keywords such as "water accumulation", "road condition", "road section", "road", "street", and the like. For predicting a congested road segment caused by traffic control, the keyword set may include keywords such as "traffic control", "road condition", "road segment", "road", "street", and the like. For the information in at least one piece of information, the word frequency of each keyword in the information can be counted, and the higher the word frequency is, the higher the score of the information is.
In some optional implementations of this embodiment, determining the score of the information based on the word frequency of the predetermined keyword set in the information includes:
step 4061, for the keywords in the predetermined keyword set, determining the word frequency reverse document frequency of the keywords in the information.
For news and microblog data, a TF-IDF (term frequency-inverse document frequency) text analysis algorithm is used for excavating water accumulation points. Taking a news or microblog as a document, and taking TF-IDF as the characteristic of the document.
Step 4062, determine the sum of the word frequency and the reverse document frequency of each keyword as the weight feature in the information.
Extracting TD-IDF value of the keyword as the weighting characteristic of the ith document, and expressing the importance of the keyword in the text, namely di＝[w1，…，w5]Wherein w is1TF-IDF, i.e. weight, w representing the first keyword5TF-IDF representing the fifth keyword. diRepresenting the weight of each keyword in the ith document.
Step 4063, determine the number of types of keywords appearing in the information as the diversity characteristic of the information.
And calculating the sum of the numbers with the keyword weight not being 0, and representing the diversity characteristics of the keyword distribution. For example, if only one keyword "water" appears in a document, the diversity characteristic is 1. If 5 kinds of keywords appear, the diversity characteristic is 5.
Step 4064, determining the weighted sum of the weighted features and the diversity features as the score of the information.
Second score of ith documentiComprises the following steps:
wherein, wkRepresenting the weight of the kth keyword, keys representing the set of keywords, and epsilon is a hyperparameter, usually taking a smaller value, to balance the diversity of the weights and distributions of the document keywords. e.g. of the typeiRepresenting the diversity characteristics of the keyword distribution in the ith document.
In this embodiment, the names of the paths mined from the trajectory information are subjected to matching analysis, and the calculation method is to use the name participles of the paths as keywords and then calculate IF-IDF scores as matching scores. The second score of the water-retention point of the document with the highest matching degree, namely the second score of the path, can be regarded as the credibility value of the water-retention point mined through the data.
And step 408, selecting a second preset number of paths from the selected first preset number of paths according to the descending order of the sum of the first score and the second score, and outputting the path names of the selected second preset number of paths.
In this embodiment, the sum of the first score and the second score is used as the score of the route. Then, a second predetermined number of paths are selected in the order of scores from high to low. Wherein the second predetermined number is less than the first predetermined number. I.e. to optimize the results of big data mining. And then outputs the result of the secondary selection. The path name can be directly output, and the path name can also be marked in a navigation map, so that the user can conveniently download and use the path name.
For example, the road name is analyzed from the track information as ' Beijing city mountain area Zhujia village railway road bridge ', the road name is divided into words to obtain ' Beijing city ', ' Lishan region ', ' Zhujia village ', ' railway road ', and ' bridge ', the weight of the words in each microblog is calculated by using TF-IDF, the obtained microblog content with the highest matching degree with the link name is ' Beijing traffic police broadcasting, influenced by rainfall, the road condition under the Beijing mountain Zhujia village railway bridge has ponding broken circuit, the Touchouzhang road ponding broken circuit cannot pass temporarily, and the vehicle is requested to detour in advance, and the ponding score of the microblog reflects the trust degree that the railway road bridge in the Zhujia village in the mountain area of Beijing city is the ponding point.
The distribution diagram of the water accumulation points in Beijing is shown in fig. 3b, wherein 500 water accumulation points are excavated from fine/first conditional user travel track data, and 122 water accumulation points are excavated from microblog data. The two water accumulation points are greatly overlapped.
As can be seen from fig. 4, compared with the embodiment corresponding to fig. 2, the flow 400 of the method for outputting information in the present embodiment represents a step of confirming the ponding path excavated by the trajectory information. Therefore, the accuracy of water spot excavation can be further improved by the scheme described in the embodiment.
With further reference to fig. 5, as an implementation of the methods shown in the above-mentioned figures, the present application provides an embodiment of an apparatus for outputting information, which corresponds to the method embodiment shown in fig. 2, and which is particularly applicable to various electronic devices.
As shown in fig. 5, the apparatus 500 for outputting information of the present embodiment includes: an acquisition unit 501, a generation unit 502, a determination unit 503, and a selection unit 504. Wherein the obtaining unit 501 is configured to obtain trajectory information of a first condition for a predetermined number of days and trajectory information of a second condition for a predetermined number of days of at least one path; the generating unit 502 is configured to generate, for a path of at least one path, a second condition trajectory feature of the path and a first condition trajectory feature of the path according to trajectory information of the second condition of the path for a predetermined number of days and trajectory information of the first condition of the path for a predetermined number of days, respectively; the determining unit 503 is configured to determine, for a path of the at least one path, a similarity between the second conditional trajectory feature of the path and the first conditional trajectory feature of the path; the selection unit 504 is configured to select a first predetermined number of paths based on the similarity, and output path names of the selected paths.
In this embodiment, specific processing of the acquiring unit 501, the generating unit 502, the determining unit 503 and the selecting unit 504 of the apparatus 500 for outputting information may refer to step 201, step 202, step 203 and step 204 in the corresponding embodiment of fig. 2.
In some optional implementations of this embodiment, the selecting unit 504 is further configured to: determining a first similarity between the second conditional track quantity feature of the path and the first conditional track quantity feature of the path; determining a second similarity between the second conditional trajectory speed feature of the path and the first conditional trajectory speed feature of the path; determining a weighted sum of the first similarity and the second similarity as a first score for the path, wherein the first score is inversely related to the similarity; and selecting a first preset number of paths from at least one path according to the sequence of the first score from high to low.
In some optional implementations of this embodiment, the trajectory information includes a trajectory number and a trajectory speed; and the generating unit 502 is further configured to: generating a second condition track quantity characteristic of the path and a second condition track speed characteristic of the path according to the track quantity and the track speed in the track information of the second condition of the preset days of the path respectively; acquiring rainfall of each first condition in the first conditions of the preset days; and dividing the track quantity and the track speed in the track information of the first condition of the preset days of the path by the rainfall of the corresponding first condition to generate a first condition track quantity characteristic of the path and a first condition track speed characteristic of the path.
In some optional implementations of the present embodiment, the apparatus 500 further comprises a modification unit (not shown) configured to: determining the difference between the maximum value and the minimum value of the track speed in the track information of the first condition of the preset days as a first condition gap coefficient; determining the difference between the maximum value and the minimum value of the track speed in the track information of the second condition of the preset days as a second condition difference coefficient; updating the first conditional track speed characteristic of the path to be the product of the first conditional track speed characteristic of the path and the first condition difference coefficient; the second conditional trajectory speed characteristic of the path is updated to be the product of the second conditional trajectory speed characteristic of the path and a second condition difference coefficient.
In some optional implementations of this embodiment, the apparatus 500 further comprises a filtering unit (not shown) configured to: acquiring at least one piece of information with the date in a preset time range; for information in at least one piece of information, determining the score of the information based on the word frequency of a preset keyword set in the information; for the path in the selected first preset number of paths, matching the path name of the path with at least one piece of information, determining the information with the highest matching degree with the path name, and determining the score of the information with the highest matching degree with the path name as the second score of the path; and selecting a second preset number of paths from the selected first preset number of paths according to the sequence of the sum of the first score and the second score from large to small, and outputting the path names of the selected second preset number of paths.
In some optional implementations of this embodiment, the filtering unit is further configured to: selecting at least one information message with a score higher than a predetermined threshold value from the at least one information message as at least one candidate information message; and for the path in the selected first predetermined number of paths, matching the path name of the path with at least one piece of candidate information.
In some optional implementations of this embodiment, the filtering unit is further configured to: for the keywords in a preset keyword set, determining the word frequency reverse file frequency of the keywords in the information; determining the sum of the word frequency reverse document frequency of each keyword as the weight characteristic in the information; determining the number of types of keywords appearing in the information as diversity characteristics in the information; determining the weighted sum of the weight characteristic and the diversity characteristic as the score of the information.
Referring now to FIG. 6, a block diagram of a computer system 600 suitable for use in implementing an electronic device (e.g., the server shown in FIG. 1) of an embodiment of the present application is shown. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the method of the present application when executed by a Central Processing Unit (CPU) 601. It should be noted that the computer readable medium described herein can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
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 embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, 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 units described in the embodiments of the present application may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a generation unit, a determination unit, and a selection unit. Where the names of the units do not in some cases constitute a limitation on the units themselves, for example, the acquiring unit may also be described as a "unit that acquires trajectory information of a first condition for a predetermined number of days and trajectory information of a second condition for the predetermined number of days of at least one route".
As another aspect, the present application also provides a computer-readable medium, which may be contained in the apparatus described in the above embodiments; or may be present separately and not assembled into the device. The computer readable medium carries one or more programs which, when executed by the apparatus, cause the apparatus to: acquiring track information of a first condition of at least one path for a predetermined number of days and track information of a second condition for a predetermined number of days; for a path in at least one path, generating a second condition track characteristic of the path and a first condition track characteristic of the path according to track information of a second condition of the path in a preset number of days and track information of a first condition of the path in a preset number of days respectively; for a path in at least one path, determining a similarity between a second conditional trajectory feature of the path and a first conditional trajectory feature of the path; a first predetermined number of paths are selected based on the similarity, and path names of the selected paths are output.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of the invention as referred to in the present application is not limited to the embodiments with a specific combination of the above-mentioned features, but also covers other embodiments with any combination of the above-mentioned features or their equivalents without departing from the inventive concept. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (15)
1. A method for outputting information, comprising:
acquiring track information of a first condition of at least one path for a preset number of days and track information of a second condition of the preset number of days;
for a path in the at least one path, generating a second condition track characteristic of the path and a first condition track characteristic of the path according to the track information of the second condition of the path on the preset days and the track information of the first condition of the path on the preset days respectively;
for a path of the at least one path, determining a similarity between a second conditional trajectory feature of the path and a first conditional trajectory feature of the path;
a first predetermined number of paths are selected based on the similarity, and path names of the selected paths are output.
2. The method of claim 1, wherein said choosing a first predetermined number of paths based on similarity comprises:
determining a first similarity between the second conditional track quantity feature of the path and the first conditional track quantity feature of the path;
determining a second similarity between the second conditional trajectory speed feature of the path and the first conditional trajectory speed feature of the path;
determining a weighted sum of the first similarity and the second similarity as a first score for the path, wherein the first score is inversely related to similarity;
and selecting a first preset number of paths from the at least one path according to the sequence of the first score from large to small.
3. The method of claim 2, wherein the trajectory information includes a number of trajectories and a trajectory speed; and
the generating the second condition track feature of the path and the first condition track feature of the path according to the track information of the second condition of the predetermined number of days and the track information of the first condition of the predetermined number of days of the path respectively includes:
generating a second condition track quantity characteristic of the path and a second condition track speed characteristic of the path according to the track quantity and the track speed in the track information of the second condition of the preset days of the path respectively;
acquiring rainfall of each first condition in the first conditions of the preset days;
and dividing the track quantity and the track speed in the track information of the first condition of the preset days of the path by the rainfall of the corresponding first condition to generate a first condition track quantity characteristic of the path and a first condition track speed characteristic of the path.
4. The method of claim 3, wherein the method further comprises:
determining the difference between the maximum value and the minimum value of the track speed in the track information of the first condition of the preset days as a first condition gap coefficient;
determining the difference between the maximum value and the minimum value of the track speed in the track information of the second condition of the preset days as a second condition gap coefficient;
updating the first conditional track speed characteristic of the path to be the product of the first conditional track speed characteristic of the path and the first condition difference coefficient;
and updating the second condition track speed characteristic of the path into the product of the second condition track speed characteristic of the path and the second condition difference coefficient.
5. The method according to one of claims 2-4, wherein the method further comprises:
acquiring at least one piece of information with the date in a preset time range;
for the information in the at least one piece of information, determining the score of the information based on the word frequency of a preset keyword set in the information;
for the path in the selected first preset number of paths, matching the path name of the path with the at least one piece of information, determining the information with the highest matching degree with the path name, and determining the score of the information with the highest matching degree with the path name as the second score of the path;
and selecting a second preset number of paths from the selected first preset number of paths according to the sequence of the sum of the first score and the second score from large to small, and outputting the path names of the selected second preset number of paths.
6. The method of claim 5, wherein said matching the path name of the path with the at least one piece of information comprises:
selecting at least one information message with a score higher than a predetermined threshold value from the at least one information message as at least one candidate information message;
and for the path in the selected first predetermined number of paths, matching the path name of the path with the at least one piece of candidate information.
7. The method of claim 5, wherein determining the score of the information based on the word frequency of the predetermined set of keywords in the information comprises:
for the keywords in a preset keyword set, determining the word frequency reverse file frequency of the keywords in the information;
determining the sum of the word frequency reverse document frequency of each keyword as the weight characteristic in the information;
determining the number of types of keywords appearing in the information as diversity characteristics in the information;
and determining the weighted sum of the weight characteristic and the diversity characteristic as the score of the information.
8. An apparatus for outputting information, comprising:
an acquisition unit configured to acquire trajectory information of a first condition for a predetermined number of days and trajectory information of a second condition for the predetermined number of days of at least one route;
a generating unit configured to generate, for a path of the at least one path, a second condition trajectory feature of the path and a first condition trajectory feature of the path according to trajectory information of the second condition of the path for the predetermined number of days and trajectory information of the first condition of the predetermined number of days, respectively;
a determination unit configured to determine, for a path of the at least one path, a similarity between a second conditional trajectory feature of the path and a first conditional trajectory feature of the path;
a selecting unit configured to select a first predetermined number of paths based on the similarity, and output path names of the selected paths.
9. The apparatus of claim 8, wherein the selection unit is further configured to:
determining a first similarity between the second conditional track quantity feature of the path and the first conditional track quantity feature of the path;
determining a second similarity between the second conditional trajectory speed feature of the path and the first conditional trajectory speed feature of the path;
determining a weighted sum of the first similarity and the second similarity as a first score for the path, wherein the first score is inversely related to similarity;
and selecting a first preset number of paths from the at least one path according to the sequence of the first score from large to small.
10. The apparatus of claim 9, wherein the trajectory information comprises a number of trajectories and a trajectory speed; and
the generation unit is further configured to:
generating a second condition track quantity characteristic of the path and a second condition track speed characteristic of the path according to the track quantity and the track speed in the track information of the second condition of the preset days of the path respectively;
acquiring rainfall of each first condition in the first conditions of the preset days;
and dividing the track quantity and the track speed in the track information of the first condition of the preset days of the path by the rainfall of the corresponding first condition to generate a first condition track quantity characteristic of the path and a first condition track speed characteristic of the path.
11. The apparatus of claim 10, wherein the apparatus further comprises a correction unit configured to:
determining the difference between the maximum value and the minimum value of the track speed in the track information of the first condition of the preset days as a first condition gap coefficient;
determining the difference between the maximum value and the minimum value of the track speed in the track information of the second condition of the preset days as a second condition gap coefficient;
updating the first conditional track speed characteristic of the path to be the product of the first conditional track speed characteristic of the path and the first condition difference coefficient;
and updating the second condition track speed characteristic of the path into the product of the second condition track speed characteristic of the path and the second condition difference coefficient.
12. The apparatus according to one of claims 9-11, wherein the apparatus further comprises a filtering unit configured to:
acquiring at least one piece of information with the date in a preset time range;
for the information in the at least one piece of information, determining the score of the information based on the word frequency of a preset keyword set in the information;
for the path in the selected first preset number of paths, matching the path name of the path with the at least one piece of information, determining the information with the highest matching degree with the path name, and determining the score of the information with the highest matching degree with the path name as the second score of the path;
and selecting a second preset number of paths from the selected first preset number of paths according to the sequence of the sum of the first score and the second score from large to small, and outputting the path names of the selected second preset number of paths.
13. The apparatus of claim 12, wherein the filtering unit is further configured to:
selecting at least one information message with a score higher than a predetermined threshold value from the at least one information message as at least one candidate information message;
and for the path in the selected first predetermined number of paths, matching the path name of the path with the at least one piece of candidate information.
14. The apparatus of claim 12, wherein the filtering unit is further configured to:
for the keywords in a preset keyword set, determining the word frequency reverse file frequency of the keywords in the information;
determining the sum of the word frequency reverse document frequency of each keyword as the weight characteristic in the information;
determining the number of types of keywords appearing in the information as diversity characteristics in the information;
and determining the weighted sum of the weight characteristic and the diversity characteristic as the score of the information.
15. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-7.
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| CN108267143A (en) * | 2016-12-30 | 2018-07-10 | 沈阳美行科技有限公司 | Navigation routine recommends method, system and its apparatus |
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