IRSEDec 2, 2017

A Context-aware Recommender System for Hyperlocal News: A Conceptual Framework

arXiv:1712.01264v1
Originality Synthesis-oriented
AI Analysis

This is an incremental approach for news readers needing localized and timely recommendations.

The paper tackles the problem of recommending hyperlocal news by proposing a conceptual framework for a mobile recommender system that addresses spatial-temporal relevance, recency, real-time updates, and validated news, with implementation discussed in a distributed file system.

Recommender systems (RSs) have been popular in variety of application domains due to the increased demand for filtering and sorting items and information. Today, there is a numerous approaches and algorithms of data filtering and recommendations. This works presents a conceptual framework for constructing a mobile RS in hyper-local news domain. The mobile RS is designed to deal with specific requirements of news readers, such as spatial- temporal relevance, recency, real-time update and validated news. The implementation of the RS in a distributed file system is also discussed.

Foundations

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