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Title: :  A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings
PaperId: :  11693
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 6 Issue 2 2020
DUI:    16.0415/IJARIIE-11693
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Suhanth PAnand institute of higher technology
Sathish Kumar GAnand institute of higher technology
Priskilla Angel Rani JAnand institute of higher technology

Abstract

Computer engineering
Point of Interest, Keyword Dominant Web Services Search Engine, Collaborative Filtering.
Tourism has become an important industry for most of the economies, especially for non-industrialized countries where it represents the main source of income. Recommendation systems are defined as the techniques used to predict the rating one individual will give to an item or social entity. These items can be places, books, movies, restaurants and things on which individuals have different preferences. These preferences are being predicted using two approaches first content-based approach which involves characteristics of an item and second collaborative filtering approaches which takes into account user's past behavior to make choices. Point of interest (POI) recommendation, which provides personalized recommendation of places to users. However, quite different from traditional interest oriented merchandise recommendation, POI recommendation is more complex due to the timing effects: we need to examine whether the POI fits a user’s availability. With increasing adoption and presence of Online services, designing novel approaches for efficient and effective recommendation has become of paramount importance. In existing services discovery and recommendation approaches focus on keyword dominant Web service search engines, which possess many limitations such as poor recommendation performance and heavy dependence on correct and complex queries from users. Recent research efforts on Online service recommendation center on two prominent approaches: collaborative filtering and content based recommendation. Unfortunately, both approaches have some drawbacks, which restrict their applicability in Web service recommendation. In proposed system for recommendation we will be using Agglomerative Hierarchal Clustering and collaborative filtering for effective recommendation in this system.

Citations

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IJARIIE Suhanth P, Sathish Kumar G, and Priskilla Angel Rani J. "A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings" International Journal Of Advance Research And Innovative Ideas In Education Volume 6 Issue 2 2020 Page 1172-1178
MLA Suhanth P, Sathish Kumar G, and Priskilla Angel Rani J. "A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings." International Journal Of Advance Research And Innovative Ideas In Education 6.2(2020) : 1172-1178.
APA Suhanth P, Sathish Kumar G, & Priskilla Angel Rani J. (2020). A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings. International Journal Of Advance Research And Innovative Ideas In Education, 6(2), 1172-1178.
Chicago Suhanth P, Sathish Kumar G, and Priskilla Angel Rani J. "A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings." International Journal Of Advance Research And Innovative Ideas In Education 6, no. 2 (2020) : 1172-1178.
Oxford Suhanth P, Sathish Kumar G, and Priskilla Angel Rani J. 'A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings', International Journal Of Advance Research And Innovative Ideas In Education, vol. 6, no. 2, 2020, p. 1172-1178. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/A_Point_of_Interest_Recommendation_Engine_for_Suggesting_Sightseeing_Spots_by_User_Reviews_and_Ratings_ijariie11693.pdf (Accessed : 20 April 2020).
Harvard Suhanth P, Sathish Kumar G, and Priskilla Angel Rani J. (2020) 'A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings', International Journal Of Advance Research And Innovative Ideas In Education, 6(2), pp. 1172-1178IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/A_Point_of_Interest_Recommendation_Engine_for_Suggesting_Sightseeing_Spots_by_User_Reviews_and_Ratings_ijariie11693.pdf (Accessed : 20 April 2020)
IEEE Suhanth P, Sathish Kumar G, and Priskilla Angel Rani J, "A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings," International Journal Of Advance Research And Innovative Ideas In Education, vol. 6, no. 2, pp. 1172-1178, Mar-App 2020. [Online]. Available: https://ijariie.com/AdminUploadPdf/A_Point_of_Interest_Recommendation_Engine_for_Suggesting_Sightseeing_Spots_by_User_Reviews_and_Ratings_ijariie11693.pdf [Accessed : 20 April 2020].
Turabian Suhanth P, Sathish Kumar G, and Priskilla Angel Rani J. "A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 6 number 2 (20 April 2020).
Vancouver Suhanth P, Sathish Kumar G, and Priskilla Angel Rani J. A Point of Interest Recommendation Engine for Suggesting Sightseeing Spots by User Reviews and Ratings. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2020 [Cited : 20 April 2020]; 6(2) : 1172-1178. Available from: https://ijariie.com/AdminUploadPdf/A_Point_of_Interest_Recommendation_Engine_for_Suggesting_Sightseeing_Spots_by_User_Reviews_and_Ratings_ijariie11693.pdf
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