| 书目名称 | Ontology-Based Data Access Leveraging Subjective Reports |
| 编辑 | Gerardo I. Simari,Cristian Molinaro,Livia Predoiu |
| 视频video | |
| 概述 | Includes supplementary material: |
| 丛书名称 | SpringerBriefs in Computer Science |
| 图书封面 |  |
| 描述 | .This SpringerBrief reviews the knowledge engineering problem of engineering objectivity in top-k query answering; essentially, answers must be computed taking into account the user’s preferences and a collection of (subjective) reports provided by other users. Most assume each report can be seen as a set of scores for a list of features, its author’s preferences among the features, as well as other information is discussed in this brief. These pieces of information for every report are then combined, along with the querying user’s preferences and their trust in each report, to rank the query results. Everyday examples of this setup are the online reviews that can be found in sites like Amazon, Trip Advisor, and Yelp, among many others..Throughout this knowledge engineering effort the authors adopt the Datalog+/– family of ontology languages as the underlying knowledge representation and reasoning formalism, and investigate several alternative ways in which rankings can b.ederived, along with algorithms for top-k (atomic) query answering under these rankings. This SpringerBrief also investigate assumptions under which our algorithms run in polynomial time in the data complexity.. |
| 出版日期 | Book 2017 |
| 关键词 | Semantic web; Knowledge engineering; Computational objectivity; Reasoning with preferences; Reasoning un |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-65229-0 |
| isbn_softcover | 978-3-319-65228-3 |
| isbn_ebook | 978-3-319-65229-0Series ISSN 2191-5768 Series E-ISSN 2191-5776 |
| issn_series | 2191-5768 |
| copyright | Springer International Publishing AG 2017 |
发表于 2025-3-21 17:50:55
