Personalized location aware recommendation system

Veningston, K.; Shanmugalakshmi, R.

doi:10.1109/icaccs.2015.7324140

Cited by 10 publications

(4 citation statements)

References 23 publications

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“…Personalisation is also considered a key component of location-based systems. In order to achieve personalisation, the system builds a model representing the user's needs and preferences, named the user model [11].…”

Section: Personalisation Of Cultural Heritage Visitsmentioning

confidence: 99%

Context-Based Cultural Visits

Assis

Andrade

Viana

2021

Advances in Intelligent Systems and Computing

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Section: Personalisation Of Cultural Heritage Visitsmentioning

confidence: 99%

Context-Based Cultural Visits

Assis

Andrade

Viana

2021

Advances in Intelligent Systems and Computing

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“…In addition, the polarity of each review's sentiment is defined only by the user's rating, and no sentiment analysis is performed in the text of the review. Veningston and Shanmugalakshmi (2015) proposed a location aware recommender system that considers personalization features to provide personalized location suggestions based on users' preferences. The system analyses location aware reviews in order to understand the community user experiences, and then, it is matched with a specific user search preference.…”

Section: Related Workmentioning

confidence: 99%

A context‐aware recommender method based on text and opinion mining

et al. 2020

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A recommender system is an information filtering technology that can be used to recommend items that may be of interest to users. Additionally, there are the contextaware recommender systems that consider contextual information to generate the recommendations. Reviews can provide relevant information that can be used by recommender systems, including contextual and opinion information. In a previous work, we proposed a context-aware recommendation method based on text mining (CARM-TM). The method includes two techniques to extract context from reviews: CIET.5 embed , a technique based on word embeddings; and RulesContext, a technique based on association rules. In this work, we have extended our previous method by including CEOM, a new technique which extracts context by using aspect-based opinions. We call our extension of CARM-TOM (context-aware recommendation method based on text and opinion mining). To generate recommendations, our method makes use of the CAMF algorithm, a context-aware recommender based on matrix factorization. To evaluate CARM-TOM, we ran an extensive set of experiments in a dataset about restaurants, comparing CARM-TOM against the MF algorithm, an uncontextual recommender system based on matrix factorization; and against a context extraction method proposed in literature. The empirical results strongly indicate that our method is able to improve a context-aware recommender system.

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“…Be that as it may, the hindrance of this framework when contrasted with seems to be, it is just founded on area based action. In our proposed framework we are giving area based pursuit just as numerous other office by which residents can look [6].…”

Section: Related Workmentioning

confidence: 99%

Health Service Recommendation as p er Citizens Requirement u sing Machine Learning and Data Mining

Karale,

Patel,

Khot

et al. 2020

IJITEE

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Citizens or patients gratification has developed a paramount quantification for evaluating the quality of hospitals in health care. This quantification has evolved along with an incipient feature: the quality of care perspective of the patient. These days, knowledge put away in hospital databases are developing in an undeniably tremendously. Examining that knowledge is vital for restorative basic leadership. It has been broadly perceived that hospital knowledge examination can prompt an upgrade of social insurance by ameliorating the exhibition of denizens or patient administration. The number of days patient stay is generally utilized result evaluate for emergency clinic asset utilization and to screen the exhibition of the clinic. It avails in productive utilization of assets and offices. The forecast structure are visually examined utilizing exactness, precision and review. It has been discovered that utilizing Process Mining as an antecedent to arrangement gives better outcomes. Patient feedback comprise of the perspectives and assessments of patients and administration clients on the consideration that they have encountered. The survey is been taken on the patient entrance itself by responding to certain inquiries, and this input can be seen by hospital additionally to check what criticism is given and it’s right or wrong. Brought together organization just as database framework is remembered for proposed framework which isn’t accessible in any of the application accessible right now.

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Personalized location aware recommendation system

Cited by 10 publications

References 23 publications

Context-Based Cultural Visits

Context-Based Cultural Visits

A context‐aware recommender method based on text and opinion mining

Health Service Recommendation as p er Citizens Requirement u sing Machine Learning and Data Mining

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