World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
7070
World Ranking
9699
National Ranking
4101

Overview

Hugo Zaragoza is affiliated with Amazon in the United States, working primarily within the field of Computer Science. Their research portfolio spans various interdisciplinary subfields, including Information Systems, Computational Theory and Mathematics, Infectious Diseases, Organic Chemistry, and Computer Vision and Pattern Recognition.

Their scholarly output features publications in several recognized venues, highlighting a diverse research scope. Notable publication venues include:

  • International Journal of Research in Education Humanities and Commerce
  • Journal of Chemical Information and Modeling
  • arXiv (Cornell University)

The recent papers authored or coauthored by Zaragoza cover a range of topics and years, illustrating ongoing contributions across different domains. These papers include:

  • "Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search," published in 2022 in arXiv (Cornell University)
  • "Bioactivity Profile Similarities to Expand the Repertoire of COVID-19 Drugs," published in 2020 in the Journal of Chemical Information and Modeling
  • "COMMUNITY MOTIVATION, ENGAGEMENT AND COMMITMENT ON CAVITE STATE UNIVERSITY TANZA CAMPUS EXTENSION SERVICES IN BARANGAY BAGTAS, TANZA, CAVITE: BASIS FOR PROPOSED ENHANCEMENT PLAN," published in 2025 in the International Journal of Research in Education Humanities and Commerce

Zaragoza's work incorporates several core topics relevant to contemporary research and application in computer science and related fields. These main topics of research are:

  • Computational Drug Discovery Methods
  • SARS-CoV-2 and COVID-19 Research
  • Synthesis and biological activity
  • Advanced Image and Video Retrieval Techniques
  • Information Retrieval and Search Behavior
  • Web Data Mining and Analysis

Their collaborative network includes frequent coauthors such as IRISH JOY G. BRIGOLI, ELIJAH V. DIZON, C. Evangelista, CLARK JAY G. DUERO, and PAULINE V. BAYRANTE. This reflects a pattern of working in multidisciplinary teams spanning different research areas.

Best Publications

  • The Probabilistic Relevance Framework

    Stephen Robertson;Hugo Zaragoza

  • Simple BM25 extension to multiple weighted fields

    Stephen Robertson;Hugo Zaragoza;Michael Taylor

  • Learning to Rank Answers on Large Online QA Collections

    Mihai Surdeanu;Massimiliano Ciaramita;Hugo Zaragoza

  • Ad-hoc object retrieval in the web of data

    Jeffrey Pound;Peter Mika;Hugo Zaragoza

  • Microsoft Cambridge at TREC 13: Web and Hard Tracks.

    Hugo Zaragoza;Nick Craswell;Michael J. Taylor;Suchi Saria

  • Relevance weighting for query independent evidence

    Nick Craswell;Stephen Robertson;Hugo Zaragoza;Michael Taylor

  • Learning to rank answers to non-factoid questions from web collections

    Mihai Surdeanu;Massimiliano Ciaramita;Hugo Zaragoza

  • The Perceptron Algorithm with Uneven Margins

    Yaoyong Li;Hugo Zaragoza;Ralf Herbrich;John Shawe-Taylor

  • Early exit optimizations for additive machine learned ranking systems

    B. Barla Cambazoglu;Hugo Zaragoza;Olivier Chapelle;Jiang Chen

  • Parsimonious language models for information retrieval

    Djoerd Hiemstra;Stephen Robertson;Hugo Zaragoza

  • Ranking very many typed entities on wikipedia

    Hugo Zaragoza;Henning Rode;Peter Mika;Jordi Atserias

  • Optimisation methods for ranking functions with multiple parameters

    Michael Taylor;Hugo Zaragoza;Nick Craswell;Stephen Robertson

  • Hits on the web: how does it compare?

    Marc A. Najork;Hugo Zaragoza;Michael J. Taylor

  • System and method for ranking search results using file types

    Dmitriy Meyerzon;Stephen Robertson;Hugo Zaragoza;Michael Taylor

  • System and method for ranking search results using click distance

    Dmitriy Meyerzon;Hugo Zaragoza

  • Bayesian extension to the language model for ad hoc information retrieval

    Hugo Zaragoza;Djoerd Hiemstra;Michael Tipping

  • Predictive user click models based on click-through history

    Benjamin Piwowarski;Hugo Zaragoza

  • Microsoft Cambridge at TREC 2002: Filtering Track.

    Stephen E. Robertson;Steve Walker;Hugo Zaragoza;Ralf Herbrich

  • Field weighting in text searching

    Stephen Robertson;Hugo Zaragoza;Michael Taylor;Stefan Isbein Larimore

  • Query graphs indicating related queries

    Eric D. Brill;Hugo Zaragoza;Robert J. Ragno;Silviu-Petru Cucerzan

  • Information Retrieval: Algorithms and Heuristics

    Hugo Zaragoza

  • Bayesian Extension to the Language Model

    H. Zaragoza;Djoerd Hiemstra;M. Tipping;S.E. Robertson

Frequent Co-Authors

Stephen Robertson
Stephen Robertson University College London
Peter Mika
Peter Mika Yahoo (United Kingdom)
Massimiliano Ciaramita
Massimiliano Ciaramita Google (United States)
Djoerd Hiemstra
Djoerd Hiemstra Radboud University
Nick Craswell
Nick Craswell Microsoft (United States)
Ricardo Baeza-Yates
Ricardo Baeza-Yates Royal Institute of Technology
Marc Najork
Marc Najork Google (United States)
Ralf Herbrich
Ralf Herbrich Hasso Plattner Institute
Eric Brill
Eric Brill Microsoft (United States)
Mihai Surdeanu
Mihai Surdeanu University of Arizona

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