Ricardo Baeza-Yates
Northeastern University
536 Papers
5.8K Citations
Ricardo Baeza-Yates is an academic researcher from Northeastern University. The author has contributed to research in topics: Computer science & Web search query. The author has an hindex of 73, co-authored 489 publications. Previous affiliations of Ricardo Baeza-Yates include Yahoo! & Universidade Federal de Minas Gerais.
Chat about Author
Papers
Wisdom of the Crowd or Wisdom of a Few? An Analysis of Users' Content Generation
TL;DR: This paper analysis of datasets from two different social networks, Facebook and Twitter, finds that a small percentage of active users and much less of all users represent 50% of the UGC, which implies that most of the wisdom comes from a few users challenging the independence assumption needed to have a wisdom of crowds.
37
Seasonal variation in the development of chilling injury in ‘O’Henry’ peaches
Reinaldo Campos-Vargas,Oscar Becerra,Ricardo Baeza-Yates,Verónica Cambiazo,Mauricio González,Lee A. Meisel,Lee A. Meisel,Ariel Orellana,Julio Retamales,Herman Silva,Herman Silva,Bruno G. Defilippi +11 more
TL;DR: There was no detectable correlation between juice content and quality attributes and physiological parameters, including skin color, flesh firmness, soluble solids content, respiration and ethylene production rates, suggesting factors other than those analyzed in this study are involved in this disorder.
36
New approaches to information management: attribute-centric data systems
Ricardo Baeza-Yates,Terry Jones,Gregory J. E. Rawlins +2 more
- 27 Sep 2000
TL;DR: This work argues for an approach to information representation based on the use of attributes and search that is organization-neutral, thereby giving a flexible substrate for anyone to build multiple simultaneous organizations.
35
Fast string matching with mismatches
TL;DR: This work describes and analyze three simple and fast algorithms on the average for solving the problem of string matching with a bounded number of mismatches: the naive algorithm, an algorithm based on the Boyer-Moore approach, and ad hoc deterministic finite automata searching.
34
Buon appetito: recommending personalized menus
Michele Trevisiol,Luca Chiarandini,Ricardo Baeza-Yates +2 more
- 01 Sep 2014
TL;DR: This paper mines restaurant reviews to extract food words, uses sentiment analysis applied to each sentence in order to compute the individual food preferences, and proposes several recommender systems to provide suggestions of food items or entire menus.