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Recommendation algorithms for unstructured big data such as text, audio, image and video

Recommendation algorithms for unstructured big data such as text, audio, image and video

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In recent times, the recommender system (RS) has played a significant role in assisting users in selecting the ideal product from a huge amount of data. The gradually increasing amount of customers, services and online information due to yielding the large data analysis can be a problem for service RSs. Approaches which are greatly successful cover a wide variety of recommendation tasks such as video, music, image, books. The recommendation algorithms require a variety of parameters to propose suggestions for new users, and this is where limitations and challenges of the RSs emerge. Recommendation algorithms for unstructured big data and their challenges are discussed in this chapter.

Chapter Contents:

  • 7.1 Recommender methods
  • 7.1.1 Content-based recommendations
  • 7.1.2 Collaborative recommendations
  • 7.1.3 Knowledge-based recommendations
  • 7.1.4 Demographic recommendations
  • 7.1.5 Hybrid recommendations
  • 7.2 Big data analytic
  • 7.2.1 Text analytics
  • 7.2.1.1 Steps for text analytics system
  • 7.2.1.2 Text recommendation using an angle-based interest model
  • 7.2.2 Audio analytics
  • 7.2.2.1 Prediction of genre-based link in a two-way graph for music recommendation
  • 7.2.2.2 Personalized tag-based social media music recommendation
  • 7.2.2.3 Graph-based quality model for music recommendation
  • 7.2.2.4 Music recommendation using acoustic features and user access patterns
  • 7.2.2.5 Learning content similarity for music recommendation
  • 7.2.3 Video analytics
  • 7.2.3.1 Real-time video-recommendation system
  • 7.2.3.2 Recommendation system for micro-video on big data
  • 7.2.4 Image analytics
  • 7.2.4.1 An images-textual hybrid recommendation system
  • 7.2.4.2 Recommendation system for styles and substitutes based on image
  • 7.2.5 Other recommender system
  • 7.2.5.1 Personalized trip advisor service
  • 7.2.5.2 Recommendation system with Hadoop Framework on big data
  • 7.3 Recommender systems: challenges and limitations
  • 7.4 Summary
  • References

Inspec keywords: image retrieval; Big Data; text analysis; recommender systems; content-based retrieval

Other keywords: image; video; recommender system; music; audio; unstructured big data; text; books; recommendation algorithms

Subjects: Information retrieval techniques; Information networks; Search engines; Information analysis and indexing; Database management systems (DBMS); Data handling techniques

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