Abstract— Itinerary planning is the important process for the travelling agencies which need to be done carefully to satisfy the requirements of the users. The satisfaction level of users can be increased by creating the itinerary planning in the customized manner by gathering the details from the users itself. There will be more burden of processing the large search space will occur where the number of POI present will be large. The time complexity and cost of processing those requests will be increased due to the large search space. And also it will be more difficult when there is a need of creating an similar type of itinerary plan to the multiple users. To overcome this problem in this work multi-user itinerary plan generation was proposed which intends to generate the multi-user customized itinerary plan by using the fuzzy-c-means clustering algorithm. In this approach, membership values are defined for clustering process. Based on the membership values of users we are clustering the users. From the experimentation result, the proposed system is used to reduce the search complexity as well as time complexity of the system.

1. An Efficient Construction of Itinerary Planning for
Multi-Users
D.Rajasekar1
1
Sri Krishna College of Engineering and Technology,
Computer Science and Engineering,
rajasekardcse@gmail.com
C.Dhanamani2
2
Sri Krishna College of Engineering and Technology,
Computer Science and Engineering,
cdhanamani@skcet.ac.in
Abstract— Itinerary planning is the important process for the travelling agencies which need to be done carefully to
satisfy the requirements of the users. The satisfaction level of users can be increased by creating the itinerary planning in
the customized manner by gathering the details from the users itself. There will be more burden of processing the large
search space will occur where the number of POI present will be large. The time complexity and cost of processing those
requests will be increased due to the large search space. And also it will be more difficult when there is a need of creating
an similar type of itinerary plan to the multiple users. To overcome this problem in this work multi-user itinerary plan
generation was proposed which intends to generate the multi-user customized itinerary plan by using the fuzzy-c-means
clustering algorithm. In this approach, membership values are defined for clustering process. Based on the membership
values of users we are clustering the users. From the experimentation result, the proposed system is used to reduce the
search complexity as well as time complexity of the system.
Index Terms— Point of Interest, MapReduce, Fuzzy C-Means Clustering, Itinerary plan, multiday itinerary
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1 INTRODUCTION
OUTE planning is a most time consuming process in the real
world which need to take under consideration more. The
itinerary planning for the popular tourist place will consumes
more time and also it needs to be analyzed the behavior of a number
of places to bring forth a better itinerary planning. The itinerary
planning generated should also include the details of interest
mentioned by the users within the budget and time mentioned by the
users to improve the user satisfaction level. Thither are many online
services are available online which offers just the packaged itinerary
planning to the users with their fixed costs and monetary value.
Merely it is having more limitations like, it cannot meet the user’s
needs and their budget and besides it will not give timely assistance
to the users. The individual who wants to go tourist place in the short
time manner cannot make use of the already available built-in
itinerary packages.
The other drawback present in this traditional itinerary planning,
construction is the engagement of the brokers who will behave as an
average between the users and the travelling agency to make the
route planning. The security need to be ruled out in order to provide
the privacy to the users. The automatic construction of the itinerary
planning will eliminate the need of users to discover their personal
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involvement to the unknown users.
Constructing the itinerary planning with the user satisfaction is the
greatest problem in the real world which contributes to an interesting
research for many of the researchers.
The itinerary planning needs to be made even with the small
number of points of interests as well. Although, the popular travel
agencies provide more dependable services to the group of users, it
lacks from the satisfying the individual users' requirements and
likewise neglected to achieve better customization level. Yet they try to
offer the best itinerary planning, it lacks from the high price of the
software. And also travelling agencies will not arrange the hotel
reservation and flight reservation services. They will simply provide
the travelling plan and the users need to select their path and plan to
pass the corresponding places by booking hotels and flights by
themselves.
The techniques offered in this work mainly concentrate on offering
the best route planning for the users with the gratification of the
constraints mentioned by the users. To accomplish this finish, the
points of interest to be inflicted by the user and the time and budget
details will be collected from them before preparing the program. The
budget and the time constraint will also collect from the users in order
to generate the user friendly plan. The generation of route planning is
automated in this work by presenting the novel concepts. And also to
improve the accuracy of the travelling plan, in this work, Fuzzy C
means clustering algorithm is presented in this study. A novel approach
presented in this work will leads to an optimized construction of an
itinerary planned with the customer Satisfaction level.
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R
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 Rajasekar is currently pursuing masters degree program in computer
science and engineering in Sri Krishna College of Engineering and
Technology, India, PH-9715506445. E-mail:rajasekardcse@gmail.com
 Dhanamani is currently working as Assistant Professor, computer science
and engineering in Sri Krishna College of Engineering and Technology,
India,E-mail: cdhanamani@skcet.ac.in

2. In the next section we will describe the itinerary planning,
construction process in the detailed manner.
2 RELATED WORKS
This part talks about the researches that have done previously
about the preparation of itinerary planning in the detailed manner.
Senjuti Basu Roy et al [1] discussed the automatic creation of
itinerary planning in an interactive manner. This study purports to
shorten the user's burden by providing the previous user feedback
visible to the users from which the most visited places is enough to
look by the current users instead of reviewing the all the points of
pursuit. This operation will be repeated by displaying the previous
results to the users until the user satisfaction level is achieved. To
enable this process, the user feedback model is enforced in this study
which intends to pile up the feedback of every user who enters into
the mesh. And also in this work, itinerary scoring semantic is
introduced which is utilized to rank the itineraries utilized by every
user in order to generate and offer an optimal route planning to the
users.
Barun Chandra et al [2] discussed at several problems occurred
during the set packing algorithm. The set packing algorithm intends
to group the objects into one for satisfying the user demand. Even so
there will be many events occur when the aims from the different
groups are taken together. The primary aim of this study is to find the
sub collection of more objects with maximum weights from the finite
group of available targets. To accomplish this end, this research work
introduces a k-set packing problem which intends to pack k objects
together. This study commences with an initial object taken into the
set based on the greedy solution and the farther aims are seen based
on the local search methodology. This work can be applied
effectively in all the works which are entirely founded on the
itinerary planning construction.
Munmun De Choudhury et al [3] discussed an automatic
expression of an itinerary planned based on social crumbs. In this
work, itinerary planning is constructed by leveraging the personal
interests of user by analysing the geo temporal bread crumps. This is
performed by extracting the details of time stamps and the image
contents of the available source information and grouping them to
get out the most wanted point of interest of many users. To
accomplish this, one must gather the photos of the popular cities and
the time path need to be built. Grounded on this time paths, the
optimized itinerary planning can be fabricated.
Hyoseok Yoon et al [4] proposed an novel mechanism for
itinerary plan construction based on the user generated GPS
trajectories. This workplace is principally utilized to help the
unfamiliar people in some seats where they wish to go for a holiday
trip. This work mainly aims to recover out the start point and the
terminal point of a position with the minimized cost and the
travelling. This is answered by collecting the multiple users' location
details based on the GPS tracking data. When the users are
submitting their queries, the query will send to the cloud server
where the multiple user location data will be present. The degree of
interest submitted by the users will be coupled with the GPS tracked
information, and the optimized itinerary planning will be fabricated.
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Maarten Clements et al [5] proposed details of discussed an
approach for monitoring the user behavior by calling the user
travelling. In this study, a novel approach is presented to predict the
user interest by examining the user tagged location based images. In
this work, Flickr tagged images are downloaded for the function of
predicting user travelling behaviors. After finding the users' point of
interest, those extracted places will be placed further to enable the
users to choose the special places that he requires to visit within a
special time point.
Chao Chen et al [8] discussed a new means to make an itinerary
planning by using the placement based information and the GPS
traces. GPS traces are used to place the crowd sourced information’s
that are the location which is mostly opted by the people to visit
often. To achieve this, in this work, the heuristic algorithms are
effectively utilized which focus to gather the user preferred locations
and interest scores.
Still all these works described above doesn’t try to achieve the
user satisfaction level. And besides the method discussed in the
related studies doesn’t try to fulfill the user requests in the fine
grained manner. The fine grained itinerary planning construction of
the group of users are implemented in our study which attempts to
make the itinerary planning with the user satisfaction level. The work
proposed in our study is hashed out in the next parts.
3 AUTOMATIC ITINERARY PLAN CONSTRUCTION
Focus of this research is to reduce the burden of travelling agents and
as well as to attain the satisfaction of users with the help of
customized itinerary plan. The itinerary plan construction is done
with the consideration of user interest points and as well as the time
and cost objectives. The multi user environment is created in this
work which is used to reduce the computational complexity. This
multi user environment is used to create the itinerary plan with the
knowledge of multiple users who are having the most similar
requirements. This grouping of users with similar requirements is
achieved by using the fuzzy c means clustering approach.
The itinerary plan construction consists of the next steps:.
1. Piling up the points of interest (POI) from the different
users
2. Group the users with similar POI in single cluster using
fuzzy c means clustering approach
3. Make the single daily itinerary using the MapReduce
programming
4. Single day itinerary has been constructed and an itinerary
index is built for efficient itinerary retrieval.
5. Book the flight and hotels for the group of users
By sticking with these steps, the better itinerary planning can
be fabricated with the constraints of reduced cost and time as
per the user demands.
3.1 Collecting the Point of Interest (POI) from the different
users
The optimized itinerary planning with the satisfaction of users
can be built by pulling together the points of interests that are
user wants to shoot the breeze. After gathering user interests,
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3. those requests will send to the server for the further
proceedings. Along with this information, the budget data will
also gather from the users. Grounded along the price level, the
flight and hotel booking is too performed.
In the server, the details of network traffic and road
information will be usable. These details will be gathered from
the various informants and that will be stored in the database
for the further proceedings. In our work, data set which
consists of Road traffic information’s are gathered from the
Google API. This information set consists of a various location
information and as well as the distance between the various
positions.
4 PROPOSED WORK
4.1 Group the Users With Similar POI in Single Cluster
using Fuzzy C Means Clustering (FCM) Approach
Initially, the user, with the similar requirement is grouped to
attain the best vacation. Fuzzy C- means clustering is
presented in our work to group the users with the similar
requirement. To accomplish this, the membership value will
be imputed to every user presents in the network, so that
users can be bunched up together based on those values. This
clustering mechanism will produce ease of booking hotel and
flight ticket process in the composite manner.
The FCM clustering algorithm is based along the distance
between the data present in the surroundings. In our study,
the data is a POI represented by the users. This algorithm
intends to organize the cluster by specifying the cluster center
initially. The information will be appended into the
corresponding cluster, if the distance between the data and the
cluster center is minimal.
4.1 Hotel Selection
In fact, hotels can be considered as a special type of POIs. It
must appear as the last POI in the itinerary. Here need to
calculate the traveling time from other POIs to the hotel POIs.
Hotel POIs do not incur access cost and their weights are set
as users’ rankings for the hotels based on the user’s
preference.
5 SIMULATION RESULTS
From the corresponding datasets, with the help of MapReduce
jobs single day itinerary can be constructed based on their
weight and shortest distance.
(a) Stop Id
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(b) Trip Id
(c) Route Id
(d) Longitude
(e) Latitude
Fig.2. Sample Datasets
Fig.3. Map Reduce Jobs
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4. Fig.4. Single day Itinerary
6 CONCLUSION
In this work, an automatic generation of route planning is executed
for the user who wants to get to the vacation trip. In our work, the
service is made out for creating the multiple day itineraries based on
the multiple user preferences. In main rule is to manage the multiple
users in an effective way. The fuzzy c means clustering mechanism
is used to cluster the users with the standardized requirements.
Membership values are very effective method for clustering the
multi-users.
7 FUTURE WORK
For the future work, multiday itinerary will be provided with
the help of itinerary index and fuzzy c-means clustering is
used for grouping the user according to their requirement
similarity. In enhancement stage, more services like hotel
selection, flight booking will be done
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