Automating readers' advisory to make book recommendations for K-12 readers

@inproceedings{Pera2014AutomatingRA,
  title={Automating readers' advisory to make book recommendations for K-12 readers},
  author={Maria Soledad Pera and Yiu-Kai Ng},
  booktitle={ACM Conference on Recommender Systems},
  year={2014}
}
The academic performance of students is affected by their reading ability, which explains why reading is one of the most important aspects of school curriculums. Promoting good reading habits among K-12 students is essential, given the enormous influence of reading on students' development as learners and members of society. In doing so, it is indispensable to provide readers with engaging and motivating reading selections. Unfortunately, existing book recommenders have failed to offer adequate… 

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References

SHOWING 1-10 OF 17 REFERENCES

Using Online Data Sources to Make Recommendations on Reading Materials for K-12 and Advanced Readers

This dissertation presents novel recommendation strategies which identify appealing reading materials that the readers can comprehend, which in turn can motivate them to read and incorporates the concept of “social trust” when making recommendations for advanced readers and suggested fiction books that match the reading ability of individual K-12 readers using the readability-analysis tool for books.

Readers' Advisory Service in the Public Library

Using the proven strategies in this newly updated, back-to-basics overview, librarians providing readers' advisory services will find the answers they need to help customers make appropriate choices.

Improving the model for interactive readers' advisory service

Readers' advisory services have seen a renaissance over the past two decades. Librarians across the country have been examining new ways to connect readers with books and to build a community of

Reconstructing Readability: Recent Developments and Recommendations in the Analysis of Text Difficulty

Largely due to technological advances, methods for analyzing readability have increased significantly in recent years. While past researchers designed hundreds of formulas to estimate the difficulty

Social book search: comparing topical relevance judgements and book suggestions for evaluation

This work uses the INEX 2011 Books and Social Search Track's collection of book descriptions from Amazon and social cataloguing site LibraryThing to compare classical IR with social book search in the context of the LibraryT Thing discussion forums where members ask for book suggestions.

CARES: a ranking-oriented CADAL recommender system

This paper presents a recommender system for CADAL digital library, namely CARES, which makes recommendations using a ranking-oriented collaborative filtering approach based on users' access logs, avoiding the problem of the lack of user ratings.

Amazon.com Recommendations: Item-to-Item Collaborative Filtering

This work compares three common approaches to solving the recommendation problem: traditional collaborative filtering, cluster models, and search-based methods, and their algorithm, which is called item-to-item collaborative filtering.

The Precursors of Reading Ability in Young Readers: Evidence From a Four-Year Longitudinal Study

We report a longitudinal study investigating the predictors of reading comprehension and word reading accuracy between the ages of 7 to 8 (UK Year 3) and 10 to 11 years (Year 6). We found that

Predicting social-tags for cold start book recommendations

A probabilistic model for inferring the most probable tags from the text of the book and how predictions based on social-tags can be combined with the traditional collaborative-filtering methods to yield superior performance with any number of ratings is described.

Improving the effectiveness of collaborative recommendation with ontology-based user profiles

This paper describes how ontological user profiles are learned, incrementally updated, and used for collaborative recommendation, and demonstrates that this recommendation algorithm offers improved coverage, diversity, personalization, and cold-start performance while at the same time enhancing recommendation accuracy.