CN113159415A - Intelligent tourist attraction route recommendation method based on mobile internet and big data analysis - Google Patents
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Abstract
The invention discloses a tourist attraction route intelligent recommendation method based on mobile internet and big data analysis, which screens candidate recommended attractions from all attractions by positioning the geographical position of a tourist in real time, screens out target recommended attractions by integrating the distance, the real-time number and the tour heat of the attractions, and recommends and navigates the tour route to the tourist, thereby realizing the intelligent recommendation and tour route navigation of the tourist at the current tourist attraction, compared with the traditional manual and manual attraction screening recommendation method, the recommendation method has high intellectualization level, high recommendation efficiency, expanded recommendation basis and improved recommendation function, so that the screened target recommended attractions can meet the near-distance recommendation, and also can consider the tour heat of the wrong tourist attraction and the sightseeing of the attractions, improve the recommendation effect and further enhance the tour experience of the tourist, the requirement of quick and comprehensive recommendation of tourists for visiting scenic spots in real time is greatly met.
Description
Technical Field
The invention belongs to the technical field of tourist attraction route recommendation, and particularly relates to an intelligent tourist attraction route recommendation method based on mobile internet and big data analysis.
Background
With the increase of the income of residents, the consumption concept of people is changed. The travel during leisure time for going out to sightseeing and vacation has become a fashion consumption of people, and meanwhile, the technology which is aroused along with emerging travel forms such as self-driving travel, self-service travel and free travel, and more people select free travel instead of travel with a travel group. For some large tourist attractions, most of the large tourist attractions comprise a plurality of tourist attractions, tourists need to screen and recommend the scenic spots to be visited at present when entering the tourist attractions, a traditional scenic spot screening and recommending method mostly performs manual screening and recommending according to scenic spot visiting route maps issued by the scenic spots, the screening and recommending mode is low in intelligentization level and screening efficiency, meanwhile, on one hand, the screening basis is that the scenic spots are screened nearby according to the distance, specifically, the scenic spots closest to the geographical position of the tourist are screened, the influence of the real-time number of the scenic spots and the visiting heat of the scenic spots on scenic spot screening is not considered, when the number of the real-time tourists of the scenic spots closest to the geographical position of the tourist is too large, the scenic spots are visited at the moment, and better visiting experience is difficult to achieve; on the other hand, for some tourists in the road, the correct tour route is difficult to find according to the scenic spot tour route map, so that the tour progress is slow, and a great amount of time for finding the route is wasted.
In conclusion, the traditional scenic spot screening and recommending method has single recommending basis and incomplete recommending function, so that the recommending effect is poor, the touring experience of the tourists is reduced, and the requirement of the tourists for quickly and comprehensively recommending scenic spots in real time cannot be met.
Disclosure of Invention
In order to overcome the defects in the background technology, the invention provides an intelligent tourist attraction route recommendation method based on mobile internet and big data analysis.
The purpose of the invention can be realized by the following technical scheme:
the intelligent tourist attraction route recommendation method based on the mobile internet and big data analysis comprises the following steps of;
s1, scenic spot statistics and geographic position acquisition in tourist attraction: counting the number of scenic spots existing in a tourist attraction area, numbering the counted scenic spots according to a preset sequence, respectively marking the number as 1,2,. once, i,. once, n, simultaneously respectively acquiring the geographical positions corresponding to the scenic spots, and further forming a scenic spot geographical position set Z (Z1, Z2,. once, zi,. once, zn) by the geographical positions corresponding to the scenic spots, wherein zi represents the geographical position corresponding to the ith scenic spot;
s2, setting a scenic spot camera: the method comprises the steps that cameras are respectively arranged in an inlet channel, an outlet channel and a tourist area corresponding to each scenic spot, wherein the camera of the inlet channel of each scenic spot is marked as an inlet camera and used for collecting face images of tourists entering the scenic spot, the camera of the outlet channel of each scenic spot is marked as an outlet camera and used for collecting face images of the tourists leaving the scenic spot, and the camera of the tourist area of each scenic spot is marked as a tourist camera and used for collecting the images of the tourists in the tourist area of each scenic spot;
s3, screening candidate recommended scenic spots of positions where tourists are located: respectively wearing the tourist wearing terminals on each tourist entering the tourist attraction, wherein a GPS positioning instrument in the tourist wearing terminals is used for positioning the geographical position of the tourist in real time, comparing the positioned geographical position of the tourist with the geographical position set of the attractions, further screening candidate recommended attractions from each attraction, counting the number of the screened candidate recommended attractions, if only one candidate recommended attraction is screened, the candidate recommended attraction is the target recommended attraction, further recommending the target recommended attraction to the tourist, simultaneously carrying out tourist route planning according to the geographical position of the target recommended attraction and the geographical position of the tourist, further carrying out the planned tourist route navigation on the tourist through a map terminal built in the tourist wearing terminals worn by the tourist, if more than one candidate recommended attraction is screened, recording the corresponding number of each candidate recommended attraction, can be written as 1, 2., j., m;
s4, constructing a tourist distance candidate recommended scenic spot distance set: recommending scenery spot correspondence according to each candidateThe method comprises the steps of obtaining the distance between the geographic position of the tourist and the corresponding geographic position of each candidate recommended scenic spot through the geographic position and the geographic position of the tourist, and forming a tourist distance candidate recommended scenic spot distance set L (L)1,l2,...,lj,...,lm)，ljThe distance between the geographic position of the tourist and the geographic position corresponding to the jth candidate recommended scenic spot is represented, and then the distance recommendation coefficient corresponding to each candidate recommended scenic spot is calculated according to the distance set of the tourist from the candidate recommended scenic spots, wherein the calculation formula is
S5, constructing a current tourist number set of the candidate recommended scenic spots: acquiring a current time point, acquiring images of tourists in each candidate recommended scenic spot touring area at the current time point through the touring camera of each candidate recommended scenic spot, further carrying out tourist number statistics on the acquired images of the tourists in each candidate recommended scenic spot touring area at the current time point, thus obtaining the number of the tourists corresponding to the current time point of each candidate recommended scenic spot, and forming a current tourist number set D (D) of the candidate recommended scenic spots1,d2,...,dj,...,dm),djThe number of the tourists corresponding to the current time point of the jth candidate recommended scenic spot is represented, and then the number recommendation coefficient of the tourists corresponding to each candidate recommended scenic spot is calculated according to the current number set of the tourists of the candidate recommended scenic spots, wherein the calculation formula is
S6, obtaining and analyzing historical tour data of the candidate recommended scenic spots: counting historical travel days corresponding to historical travel time periods from preset historical travel time periods, numbering the counted historical travel days according to the sequence of travel times, sequentially marking the historical travel days as 1,2, aThe acquisition time point corresponding to each visitor's face image acquired by the entrance camera in each historical tourism day and the acquisition time point corresponding to each visitor's face image acquired by the exit camera in each historical tourism day, at the moment, according to the serial number sequence of the historical tourism days, matching each visitor's face image acquired by the entrance camera of each candidate recommended scenic spot in each historical tourism day with each visitor's face image acquired by the exit camera of the candidate recommended scenic spot in the historical tourism day, thereby obtaining the visitor's face image acquired by the exit camera of the candidate recommended scenic spot in the historical tourism day which is matched with each visitor's face image acquired by the entrance camera of each candidate recommended scenic spot in each historical tourism day, and further according to the acquisition time point corresponding to two visitor's face images matched with each candidate recommended scenic spot in each historical tourism day, calculating the tour duration corresponding to each visitor of each candidate recommended scenic spot in each historical tour day, counting the number of visitors corresponding to each candidate recommended scenic spot in each historical tour day, and forming a set Y of the number of the visitors in the history of the candidate recommended scenic spotsj(yj1,yj2,...,yjk,...,yjr)，yjk is the number of tourists corresponding to the jth candidate recommended scenic spot in the kth historical tourism day, and meanwhile, the number of each tourist corresponding to each candidate recommended scenic spot in each historical tourism day is marked as 1,2, a, x, so that the touring duration corresponding to each tourist in each historical tourism day of each candidate recommended scenic spot forms a candidate recommended scenic spot historical touring duration set Tj k(tj k1,tj k2,...,tj ka,...,tj kx),tj ka represents the tour duration corresponding to the a th tourist in the kth historical tour day of the jth candidate recommended scenic spot;
s7, calculating the visit popularity indexes of the candidate recommended scenic spots: the method comprises the steps of counting the average number of tourists corresponding to each candidate recommended sight spot in a historical tourism time period according to a candidate recommended sight spot historical tourist number set, counting the average tourism time length corresponding to each candidate recommended sight spot in the historical tourism time period according to a candidate recommended sight spot historical tourist time length set, and further counting the tourism popularity index corresponding to each candidate recommended sight spot according to the average number of tourists corresponding to each candidate recommended sight spot in the historical tourism time period, the candidate recommended sight spot historical tourist number set, the average tourism time length corresponding to each candidate recommended sight spot in the historical tourism time period and the candidate recommended sight spot historical tourist time length set;
s8, screening target recommended scenic spots: counting a comprehensive recommendation coefficient corresponding to each candidate recommended scenic spot according to a distance recommendation coefficient, a tourist number recommendation coefficient and a tour popularity index corresponding to each candidate recommended scenic spot, sequencing each candidate recommended scenic spot according to the descending order of the corresponding comprehensive recommendation coefficient to obtain a sequencing result of each candidate recommended scenic spot, and further extracting the candidate recommended scenic spot with the largest comprehensive recommendation coefficient from the sequencing result, wherein the candidate recommended scenic spot is marked as a target recommended scenic spot;
s9, target recommendation of scenic spot tour route navigation: recommending the target recommended scenic spot to the tourist, planning a tour route according to the geographic position of the target recommended scenic spot and the geographic position of the tourist, and navigating the planned tour route for the tourist through a map navigation terminal built in a tour wearing terminal worn by the tourist.
Preferably, the tourism wearing terminal is internally provided with a GPS locator and a map navigation terminal, wherein the GPS locator is used for locating the geographic position of the tourist in real time, and the map navigation terminal is used for navigating the planned tourism route.
Preferably, in S3, the geographic position of the located visitor is compared with the set of geographic positions of the attractions, and then candidate recommended attractions are screened from each attraction, where the specific screening method includes the following steps:
the method comprises the following steps: taking the geographic position of the tourist as the center of a circle and taking the preset nearby visiting distance as the radius to make a nearby visiting area circle;
step two: and analyzing whether the geographic position corresponding to each sight spot is distributed in or on the nearby tour area circle, if the geographic position corresponding to a certain sight spot is distributed in or on the nearby tour area circle, reserving the sight spot, and if the geographic position corresponding to a certain sight spot is distributed outside the nearby tour area circle, rejecting the sight spot, thereby recording the reserved sight spots as candidate recommended sight spots.
Preferably, in S5, the number of the collected visitor images of each candidate recommended-sight-spot tour area at the current time point is counted, and the specific statistical method is to extract face contours of the visitor images of each candidate recommended-sight-spot tour area at the current time point, and then count the number of the face contours extracted from the visitor images of each candidate recommended-sight-spot tour area at the current time point, where the number of the face contours is the number of the visitors corresponding to the current time point of each candidate recommended-sight-spot.
Preferably, the method for calculating the tour duration corresponding to each visitor in each historical tour day for each candidate recommended scenic spot is to subtract the acquisition time point corresponding to the visitor's face image acquired by the entrance camera when the visitor enters the scenic spot from the acquisition time point corresponding to the visitor's face image acquired by the exit camera when each visitor leaves the scenic spot in each historical tour day for each candidate recommended scenic spot.
Preferably, the calculation formula of the average number of tourists corresponding to each candidate recommended scenic spot in the historical tourism time period is
In the formula
And the average number of tourists corresponding to the jth candidate recommended sight spot in the historical tourism time period is represented.
Preferably, the calculation formula of the average tour duration corresponding to the visitor of each candidate recommended sight spot in the historical tour time period is
In the formula
And the average tour duration corresponding to the visitor of the jth candidate recommended sight spot in the historical tour time period is represented.
Preferably, the statistical process of the tour popularity index corresponding to each candidate recommended sight spot is as follows:
f1, screening the maximum number of tourists corresponding to each candidate recommended scenic spot in the historical tourism time period from the set of the historical number of tourists of the candidate recommended scenic spots, and recording the maximum number as yjmax；
F2, screening the longest tour duration corresponding to each candidate recommended sight spot in the historical tour time period from the historical tour duration set of the tourists of the candidate recommended sight spots, and recording the longest tour duration as tjmax；
F3, calculating the tourism popularity index corresponding to each candidate recommended sight spot according to the maximum number of tourists, the longest tourism duration, the average number of tourists and the average tourism duration corresponding to each candidate recommended sight spot in the historical tourism time period, wherein the calculation formula is
Preferably, the calculation formula of the comprehensive recommendation coefficient corresponding to each candidate recommended sight spot is
In the formula
Expressed as the comprehensive recommendation coefficient, epsilon, corresponding to the jth candidate recommended sight spotj、χj、ηjThe recommendation weight factors are respectively expressed as a distance recommendation coefficient, a tourist number recommendation coefficient and a tour popularity index corresponding to the jth candidate recommended scenic spot, and a, b and c are respectively expressed as recommendation weight factors corresponding to the distance, the tourist number and the tour popularity.
Preferably, the corresponding size relationship of a, b and c is c > b > a.
The invention has the following beneficial effects:
(1) the invention selects candidate recommended scenic spots from the scenic spots by obtaining the geographic position corresponding to each scenic spot in the scenic spot and the real-time geographic position of the tourist, respectively carries out distance statistics, current time point tourist number statistics and tourism popularity index statistics on each candidate recommended scenic spot, calculates the comprehensive recommendation coefficient corresponding to each candidate recommended scenic spot by synthesizing the above statistical results, sorts each candidate recommended scenic spot according to the comprehensive recommendation coefficient, extracts the candidate recommended scenic spot with the maximum comprehensive recommendation coefficient from the comprehensive recommended scenic spots to carry out current tourist sight spot recommendation on the tourist, realizes the intelligent recommendation on the current tourist sightseeing spot of the tourist, compared with the traditional manual scenic spot screening recommendation method, the recommendation method has high intelligentization level and recommendation efficiency, and expands the recommendation basis, so that the selected target recommended scenic spot can meet the near distance recommendation principle, and the visiting enthusiasm of the crosspeak sightseeing and the scenic spots can be considered, the recommendation effect is improved, the visiting experience of the tourists is further enhanced, and the quick and comprehensive recommendation requirement of the tourists for visiting the scenic spots in real time is greatly met.
(2) After the target recommended scenic spot is recommended to the tourist, the tourist route of the target recommended scenic spot is planned according to the geographical position of the target recommended scenic spot and the geographical position of the tourist, and the tourist is navigated according to the planned tourist route by the map navigation terminal built in the tourist wearing terminal worn by the tourist, so that the tourist route of the target recommended scenic spot is navigated, the tourist can conveniently and quickly reach the target recommended scenic spot according to the navigated tourist route, the situation that the tourist cannot find the correct tourist route is avoided, a great amount of route searching time is saved, and the tourist progress is accelerated.
(3) In the process of counting the tourism popularity indexes corresponding to the candidate recommended scenic spots, the number condition of tourists and the tourism time condition of the tourist attractions in the historical tourism time period are fully fused, and the problems that the tourism popularity indexes are not comprehensive and not practical due to the fact that the tourism popularity indexes are counted only according to the number condition of the tourists of the candidate recommended scenic spots in the historical tourism time period are avoided, and authenticity and reliability of a counting result are affected are solved.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a flow chart of the method steps of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the intelligent tourist attraction route recommendation method based on mobile internet and big data analysis comprises the following steps;
s1, scenic spot statistics and geographic position acquisition in tourist attraction: counting the number of scenic spots existing in a tourist attraction area, numbering the counted scenic spots according to a preset sequence, respectively marking the number as 1,2,. once, i,. once, n, simultaneously respectively acquiring the geographical positions corresponding to the scenic spots, and further forming a scenic spot geographical position set Z (Z1, Z2,. once, zi,. once, zn) by the geographical positions corresponding to the scenic spots, wherein zi represents the geographical position corresponding to the ith scenic spot;
s2, setting a scenic spot camera: the method comprises the steps that cameras are respectively arranged in an inlet channel, an outlet channel and a tourist area corresponding to each scenic spot, wherein the camera of the inlet channel of each scenic spot is marked as an inlet camera and used for collecting face images of tourists entering the scenic spot, the camera of the outlet channel of each scenic spot is marked as an outlet camera and used for collecting face images of the tourists leaving the scenic spot, and the camera of the tourist area of each scenic spot is marked as a tourist camera and used for collecting the images of the tourists in the tourist area of each scenic spot;
in the embodiment, the arrangement of the plurality of cameras of each scenic spot provides a statistical basis for the subsequent statistics of the number of tourists at the current time point of the scenic spot and the touring duration of the tourists at the historical tourism time period of the scenic spot;
s3, screening candidate recommended scenic spots of positions where tourists are located: the tourist attraction management method comprises the following steps that tourists entering a tourist attraction area are respectively worn by a touring wearing terminal, a GPS positioning instrument and a map navigation terminal are arranged in the touring wearing terminal, the GPS positioning instrument is used for positioning the geographic position of the tourists in real time, the map navigation terminal is used for navigating a planned touring route, the geographic position of the tourists positioned by the GPS positioning instrument is compared with a scenic spot geographic position set, and then candidate recommended scenic spots are screened from the scenic spots, and the specific screening method comprises the following steps:
the method comprises the following steps: taking the geographic position of the tourist as the center of a circle and taking the preset nearby visiting distance as the radius to make a nearby visiting area circle;
step two: respectively calculating the linear distance between the geographic position and the circle center corresponding to each scenic spot, comparing the calculated result with a preset nearby tour distance, if the linear distance between the geographic position and the circle center corresponding to a certain scenic spot is less than or equal to the preset nearby tour distance, distributing the geographic position corresponding to the scenic spot in or on the nearby tour area circle, and if the linear distance between the geographic position and the circle center corresponding to a certain scenic spot is greater than the preset nearby tour distance, distributing the geographic position corresponding to the scenic spot outside the nearby tour area circle;
step three: if the geographic position corresponding to a certain scenic spot is distributed in or on the circle of the nearby visiting area, the scenic spot is reserved, and if the geographic position corresponding to the certain scenic spot is distributed outside the circle of the nearby visiting area, the scenic spot is removed, so that the reserved scenic spot is marked as a candidate recommended scenic spot;
counting the number of the screened candidate recommended scenic spots, wherein if only one number of the screened candidate recommended scenic spots is available, the candidate recommended scenic spot is a target recommended scenic spot, and is recommended to the tourist, and meanwhile, tour route planning is carried out according to the geographic position where the target recommended scenic spot is located and the geographic position where the tourist is located, and then the tourist is subjected to planned tour route navigation through a map navigation terminal built in a tour wearing terminal worn by the tourist, and if the number of the screened candidate recommended scenic spots is not only one, the number corresponding to each candidate recommended scenic spot is recorded and can be recorded as 1,2, a.
According to the method, the screening range is defined for screening of the later-stage target recommended scenic spots through the screened candidate recommended scenic spots, and compared with the screening of the target recommended scenic spots from all scenic spots, the screening of the candidate recommended scenic spots reduces the screening range for screening of the target recommended scenic spots, and is favorable for screening the target recommended scenic spots with the best recommending effect;
s4, constructing a tourist distance candidate recommended scenic spot distance set: obtaining the distance between the geographic position of the tourist and the corresponding geographic position of each candidate recommended scenic spot according to the corresponding geographic position of each candidate recommended scenic spot and the geographic position of the tourist, and forming a tourist distance candidate recommended scenic spot distance set L (L)1,l2,...,lj,...,lm)，ljThe distance between the geographic position of the tourist and the geographic position corresponding to the jth candidate recommended scenic spot is represented, and then the distance recommendation coefficient corresponding to each candidate recommended scenic spot is calculated according to the distance set of the tourist from the candidate recommended scenic spots, wherein the calculation formula is
The shorter the distance between the geographic position of the tourist and the geographic position corresponding to a candidate recommended scenic spot is, the larger the distance recommendation coefficient corresponding to the candidate recommended scenic spot is;
s5, constructing a current tourist number set of the candidate recommended scenic spots: acquiring a current time point, acquiring tourist images of each candidate recommended scenic spot tourist area at the current time point through a tourist camera of each candidate recommended scenic spot, and further performing tourist number statistics on the acquired tourist images of each candidate recommended scenic spot tourist area at the current time point1,d2,...,dj,...,dm),djThe number of the tourists corresponding to the current time point of the jth candidate recommended scenic spot is represented, and then the number recommendation coefficient of the tourists corresponding to each candidate recommended scenic spot is calculated according to the current number set of the tourists of the candidate recommended scenic spots, wherein the calculation formula is
The number of tourists corresponding to the current time point of each candidate recommended scenic spot is smaller, and the recommendation coefficient of the number of the tourists corresponding to the candidate recommended scenic spot is larger;
s6, obtaining and analyzing historical tour data of the candidate recommended scenic spots: counting historical travel days corresponding to historical travel time periods from preset historical travel time periods, numbering the counted historical travel days according to the sequence of travel times, sequentially marking the historical travel days as 1,2, a Matching the acquired face images of the tourists to obtain the face images of the tourists acquired by the outlet camera of the candidate recommended scenic spot in the historical tourism day, which are matched with the face images of the tourists acquired by the inlet camera of the candidate recommended scenic spot in the historical tourism day, calculating the corresponding touring duration of each visitor of the candidate recommended scenic spot in each historical tourism day according to the acquisition time points corresponding to the two face images of the candidate recommended scenic spot matched with each historical tourism day, wherein the calculation method is that the acquisition time point corresponding to the situation that the visitor acquires the face image of each visitor when each visitor leaves the scenic spot in each historical tourism day of each candidate recommended scenic spot is subtracted by the acquisition time point corresponding to the situation that the visitor acquires the face imageWhen entering the scenic spot, the corresponding acquisition time point is acquired by the inlet camera when the face image of the tourist is acquired, at the moment, the number of the tourists corresponding to each candidate recommended scenic spot in each historical tourist day is counted, and the number is formed into a set Y of the historical number of the tourists of the candidate recommended scenic spotj(yj1,yj2,...,yjk,...,yjr)，yjk is the number of tourists corresponding to the jth candidate recommended scenic spot in the kth historical tourism day, and meanwhile, the number of each tourist corresponding to each candidate recommended scenic spot in each historical tourism day is marked as 1,2, a, x, so that the touring duration corresponding to each tourist in each historical tourism day of each candidate recommended scenic spot forms a candidate recommended scenic spot historical touring duration set Tj k(tj k1,tj k2,...,tj ka,...,tj kx),tj ka represents the tour duration corresponding to the a th tourist in the kth historical tour day of the jth candidate recommended scenic spot;
s7, calculating the visit popularity indexes of the candidate recommended scenic spots: according to the historical tourist number set of the candidate recommended scenic spots, the average tourist number corresponding to each candidate recommended scenic spot in the historical tourist time period is counted
In the formula
The number of the average visitors corresponding to the jth candidate recommended sight spot in the historical tourism time period is represented, and the average tourism time length corresponding to the visitors of each candidate recommended sight spot in the historical tourism time period is counted according to the historical tourism time length set of the candidate recommended sight spots
In the formula
The average tour duration corresponding to the visitor of the jth candidate recommended sight spot in the historical tour time period is represented, and then the historical tourism duration of each candidate recommended sight spot isThe method comprises the following steps of counting a tourism popularity index corresponding to each candidate recommended scenic spot by an average tourist number corresponding to a tourist time period, a set of a historical tourist number of the candidate recommended scenic spots, an average tourism duration corresponding to the tourist in the historical tourist time period of each candidate recommended scenic spot and a set of the historical tourism duration of the candidate recommended scenic spot, wherein the counting process is as follows:
f1, screening the maximum number of tourists corresponding to each candidate recommended scenic spot in the historical tourism time period from the set of the historical number of tourists of the candidate recommended scenic spots, and recording the maximum number as yjmax；
F2, screening the longest tour duration corresponding to each candidate recommended sight spot in the historical tour time period from the historical tour duration set of the tourists of the candidate recommended sight spots, and recording the longest tour duration as tjmax；
F3, calculating the tourism popularity index corresponding to each candidate recommended sight spot according to the maximum number of tourists, the longest tourism duration, the average number of tourists and the average tourism duration corresponding to each candidate recommended sight spot in the historical tourism time period, wherein the calculation formula is
In the embodiment, in the process of counting the tourism popularity indexes corresponding to the candidate recommended scenic spots, the number condition of tourists and the tourism time condition of the candidate recommended scenic spots in the historical tourism time period are fully fused, and the problems that the tourism popularity indexes are not comprehensive and not practical due to the fact that the tourism popularity indexes are counted only according to the number condition of the tourists of the candidate recommended scenic spots in the historical tourism time period are avoided, and the authenticity and the reliability of a counting result are influenced;
s8, screening target recommended scenic spots: according to the distance recommendation coefficient, the number recommendation coefficient and the tourism popularity index corresponding to each candidate recommended scenic spot, counting the comprehensive recommendation coefficient corresponding to each candidate recommended scenic spot
In the formula
Is shown asThe comprehensive recommendation coefficient epsilon corresponding to the jth candidate recommended scenic spotj、χj、ηjRespectively representing a distance recommendation coefficient, a tourist number recommendation coefficient and a tour popularity index corresponding to the jth candidate recommended scenic spot, wherein a, b and c respectively represent recommendation weight factors corresponding to the distance, the tourist number and the tour popularity, the corresponding size relationship of a, b and c is that c is larger than b and larger than a, sequencing each candidate recommended scenic spot according to the sequence of the corresponding comprehensive recommendation coefficient from large to small to obtain the sequencing result of each candidate recommended scenic spot, further extracting the candidate recommended scenic spot with the maximum comprehensive recommendation coefficient from the sequencing result, and marking the candidate recommended scenic spot as a target recommended scenic spot;
in the embodiment, distance statistics, current time point tourist number statistics and touring popularity index statistics are carried out on each candidate recommended scenic spot, so that a comprehensive recommendation coefficient corresponding to each candidate recommended scenic spot is calculated by synthesizing the statistical results, meanwhile, each candidate recommended scenic spot is ranked according to the comprehensive recommendation coefficient, and a candidate recommended point with the largest comprehensive recommendation coefficient is extracted from the comprehensive recommended coefficients to carry out current tourist scenic spot recommendation on the tourist, so that intelligent recommendation on the tourist's current tourist scenic spot is realized. The requirement of quick and comprehensive recommendation of tourists for visiting scenic spots in real time is greatly met;
s9, target recommendation of scenic spot tour route navigation: recommend the sight spot of target recommendation for this visitor, carry out the route planning of touring according to the geographical position that this sight spot of target recommendation is located and this visitor's geographical position simultaneously, and then through the built-in map navigation terminal of touring wearing terminal that this visitor worn and to carry out the route navigation of planning to this visitor, realized the route navigation of touring to the sight spot of target recommendation, be convenient for the visitor arrive the sight spot of target recommendation according to the route of touring of navigation fast, avoided the emergence of some unskilled tourists can't find the exact route condition of touring, perfect the recommendation function of current sight spot of touring, the time of having practiced thrift a large amount of seeks the route, and then accelerated the touring progress.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (10)
1. The intelligent tourist attraction route recommendation method based on the mobile internet and the big data analysis is characterized by comprising the following steps of;
s1, scenic spot statistics and geographic position acquisition in tourist attraction: counting the number of scenic spots existing in a tourist attraction area, numbering the counted scenic spots according to a preset sequence, respectively marking the number as 1,2,. once, i,. once, n, simultaneously respectively acquiring the geographical positions corresponding to the scenic spots, and further forming a scenic spot geographical position set Z (Z1, Z2,. once, zi,. once, zn) by the geographical positions corresponding to the scenic spots, wherein zi represents the geographical position corresponding to the ith scenic spot;
s2, setting a scenic spot camera: the method comprises the steps that cameras are respectively arranged in an inlet channel, an outlet channel and a tourist area corresponding to each scenic spot, wherein the camera of the inlet channel of each scenic spot is marked as an inlet camera and used for collecting face images of tourists entering the scenic spot, the camera of the outlet channel of each scenic spot is marked as an outlet camera and used for collecting face images of the tourists leaving the scenic spot, and the camera of the tourist area of each scenic spot is marked as a tourist camera and used for collecting the images of the tourists in the tourist area of each scenic spot;
s3, screening candidate recommended scenic spots of positions where tourists are located: respectively wearing the tourist wearing terminals on each tourist entering the tourist attraction, wherein a GPS positioning instrument in the tourist wearing terminals is used for positioning the geographical position of the tourist in real time, comparing the positioned geographical position of the tourist with the geographical position set of the attractions, further screening candidate recommended attractions from each attraction, counting the number of the screened candidate recommended attractions, if only one candidate recommended attraction is screened, the candidate recommended attraction is the target recommended attraction, further recommending the target recommended attraction to the tourist, simultaneously carrying out tourist route planning according to the geographical position of the target recommended attraction and the geographical position of the tourist, further carrying out the planned tourist route navigation on the tourist through a map terminal built in the tourist wearing terminals worn by the tourist, if more than one candidate recommended attraction is screened, recording the corresponding number of each candidate recommended attraction, can be written as 1, 2., j., m;
s4, constructing a tourist distance candidate recommended scenic spot distance set: obtaining the distance between the geographic position of the tourist and the corresponding geographic position of each candidate recommended scenic spot according to the corresponding geographic position of each candidate recommended scenic spot and the geographic position of the tourist, and forming a tourist distance candidate recommended scenic spot distance set L (L)1,l2,...,lj,...,lm)，ljThe distance between the geographic position of the tourist and the geographic position corresponding to the jth candidate recommended scenic spot is represented, and then the distance recommendation coefficient corresponding to each candidate recommended scenic spot is calculated according to the distance set of the tourist from the candidate recommended scenic spots, wherein the calculation formula is
S5, constructing a current tourist number set of the candidate recommended scenic spots: acquiring a current time point, acquiring images of tourists in each candidate recommended scenic spot touring area at the current time point through the touring camera of each candidate recommended scenic spot, further carrying out tourist number statistics on the acquired images of the tourists in each candidate recommended scenic spot touring area at the current time point, thus obtaining the number of the tourists corresponding to the current time point of each candidate recommended scenic spot, and forming a current tourist number set D (D) of the candidate recommended scenic spots1,d2,...,dj,...,dm),djThe number of the tourists corresponding to the current time point of the jth candidate recommended scenic spot is represented, and then the number recommendation coefficient of the tourists corresponding to each candidate recommended scenic spot is calculated according to the current number set of the tourists of the candidate recommended scenic spots, wherein the calculation formula is
S6, obtaining and analyzing historical tour data of the candidate recommended scenic spots: counting historical travel days corresponding to historical travel time periods from preset historical travel time periods, numbering the counted historical travel days according to the sequence of travel times, sequentially marking the historical travel days as 1,2, a Matching the acquired face images of the tourists to obtain the face images of the tourists acquired by the outlet camera of the candidate recommended scenic spot in the historical tourism day, which are matched with the face images of the tourists acquired by the inlet camera of the candidate recommended scenic spot in the historical tourism day, calculating the tourism duration corresponding to each visitor of each candidate recommended scenic spot in each historical tourism day according to the acquisition time points corresponding to the two face images of the tourists acquired by the candidate recommended scenic spot in each historical tourism day, counting the number of the tourists corresponding to each candidate recommended scenic spot in each historical tourism day, and forming a set Y of the number of the tourists of the candidate recommended scenic spot historyj(yj1,yj2,...,yjk,...,yjr)，yjk is the number of tourists corresponding to the jth candidate recommended scenic spot in the kth historical tourism day, and meanwhile, the number of each tourist corresponding to each candidate recommended scenic spot in each historical tourism day is marked as 1,2, a, x, so that the touring duration corresponding to each tourist in each historical tourism day of each candidate recommended scenic spot forms the tourism duration of each tourist in each historical tourism day of the candidate recommended scenic spotVisit duration set Tj k(tj k1,tj k2,...,tj ka,...,tj kx),tj ka represents the tour duration corresponding to the a th tourist in the kth historical tour day of the jth candidate recommended scenic spot;
s7, calculating the visit popularity indexes of the candidate recommended scenic spots: the method comprises the steps of counting the average number of tourists corresponding to each candidate recommended sight spot in a historical tourism time period according to a candidate recommended sight spot historical tourist number set, counting the average tourism time length corresponding to each candidate recommended sight spot in the historical tourism time period according to a candidate recommended sight spot historical tourist time length set, and further counting the tourism popularity index corresponding to each candidate recommended sight spot according to the average number of tourists corresponding to each candidate recommended sight spot in the historical tourism time period, the candidate recommended sight spot historical tourist number set, the average tourism time length corresponding to each candidate recommended sight spot in the historical tourism time period and the candidate recommended sight spot historical tourist time length set;
s8, screening target recommended scenic spots: counting a comprehensive recommendation coefficient corresponding to each candidate recommended scenic spot according to a distance recommendation coefficient, a tourist number recommendation coefficient and a tour popularity index corresponding to each candidate recommended scenic spot, sequencing each candidate recommended scenic spot according to the descending order of the corresponding comprehensive recommendation coefficient to obtain a sequencing result of each candidate recommended scenic spot, and further extracting the candidate recommended scenic spot with the largest comprehensive recommendation coefficient from the sequencing result, wherein the candidate recommended scenic spot is marked as a target recommended scenic spot;
s9, target recommendation of scenic spot tour route navigation: recommending the target recommended scenic spot to the tourist, planning a tour route according to the geographic position of the target recommended scenic spot and the geographic position of the tourist, and navigating the planned tour route for the tourist through a map navigation terminal built in a tour wearing terminal worn by the tourist.
2. The intelligent tourist attraction route recommendation method based on mobile internet and big data analysis as claimed in claim 1, wherein: the tourism wearing terminal is internally provided with a GPS (global positioning system) locator and a map navigation terminal, wherein the GPS locator is used for positioning the geographic position of a tourist in real time, and the map navigation terminal is used for navigating a planned tourism route.
3. The intelligent tourist attraction route recommendation method based on mobile internet and big data analysis as claimed in claim 1, wherein: in the step S3, the geographic position of the located visitor is compared with the set of geographic positions of the scenic spots, and then candidate recommended scenic spots are screened from each scenic spot, wherein the specific screening method includes the following steps:
the method comprises the following steps: taking the geographic position of the tourist as the center of a circle and taking the preset nearby visiting distance as the radius to make a nearby visiting area circle;
step two: and analyzing whether the geographic position corresponding to each sight spot is distributed in or on the nearby tour area circle, if the geographic position corresponding to a certain sight spot is distributed in or on the nearby tour area circle, reserving the sight spot, and if the geographic position corresponding to a certain sight spot is distributed outside the nearby tour area circle, rejecting the sight spot, thereby recording the reserved sight spots as candidate recommended sight spots.
4. The intelligent tourist attraction route recommendation method based on mobile internet and big data analysis as claimed in claim 1, wherein: in S5, the number of collected tourist images in each candidate recommended scenic spot tourist area at the current time point is counted, and the specific statistical method is to extract face contours from the tourist images in each candidate recommended scenic spot tourist area at the current time point, and further count the number of face contours extracted from the tourist images in each candidate recommended scenic spot tourist area at the current time point, where the number of face contours is the number of tourists corresponding to each candidate recommended scenic spot current time point.
5. The intelligent tourist attraction route recommendation method based on mobile internet and big data analysis as claimed in claim 1, wherein: the method for calculating the tour duration corresponding to each visitor in each historical tour day of each candidate recommended scenic spot is to subtract the corresponding acquisition time point when the face image of each visitor is acquired by the inlet camera when each visitor leaves the scenic spot from the acquisition time point corresponding to the face image of each visitor when the visitor enters the scenic spot.
6. The intelligent tourist attraction route recommendation method based on mobile internet and big data analysis as claimed in claim 1, wherein: the calculation formula of the average number of tourists corresponding to each candidate recommended scenic spot in the historical tourism time period is
In the formula
And the average number of tourists corresponding to the jth candidate recommended sight spot in the historical tourism time period is represented.
7. The intelligent tourist attraction route recommendation method based on mobile internet and big data analysis as claimed in claim 1, wherein: the calculation formula of the average tour duration corresponding to the tourists of each candidate recommended scenic spot in the historical tour time period is
In the formula
And the average tour duration corresponding to the visitor of the jth candidate recommended sight spot in the historical tour time period is represented.
8. The intelligent tourist attraction route recommendation method based on mobile internet and big data analysis as claimed in claim 1, wherein: the statistical process of the tour popularity index corresponding to each candidate recommended scenic spot is as follows:
f1, screening out historical tourists of each candidate recommended scenic spot from the historical tourist number set of the candidate recommended scenic spotsThe corresponding maximum number of tourists in the travel time period is recorded as yjmax；
F2, screening the longest tour duration corresponding to each candidate recommended sight spot in the historical tour time period from the historical tour duration set of the tourists of the candidate recommended sight spots, and recording the longest tour duration as tjmax；
F3, calculating the tourism popularity index corresponding to each candidate recommended sight spot according to the maximum number of tourists, the longest tourism duration, the average number of tourists and the average tourism duration corresponding to each candidate recommended sight spot in the historical tourism time period, wherein the calculation formula is
9. The intelligent tourist attraction route recommendation method based on mobile internet and big data analysis as claimed in claim 1, wherein: the calculation formula of the comprehensive recommendation coefficient corresponding to each candidate recommended scenic spot is
In the formula
Expressed as the comprehensive recommendation coefficient, epsilon, corresponding to the jth candidate recommended sight spotj、χj、ηjThe recommendation weight factors are respectively expressed as a distance recommendation coefficient, a tourist number recommendation coefficient and a tour popularity index corresponding to the jth candidate recommended scenic spot, and a, b and c are respectively expressed as recommendation weight factors corresponding to the distance, the tourist number and the tour popularity.
10. The intelligent tourist attraction route recommendation method based on mobile internet and big data analysis as claimed in claim 9, wherein: the corresponding size relationship of a, b and c is that c is more than b and more than a.
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