![Ontology-based data access leveraging subjective reports [electronic resource]](https://image.aladin.co.kr/product/11330/85/cover/3319652281_2.jpg)
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| 005 | 20190719091902 | |
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| 008 | 190708s2017 sz a ob 000 0 eng d | |
| 020 | ▼a 9783319652283 | |
| 020 | ▼a 9783319652290 (e-book) | |
| 040 | ▼a 211009 ▼c 211009 ▼d 211009 | |
| 050 | 4 | ▼a QA75.5-76.95 |
| 082 | 0 4 | ▼a 006.3/32 ▼2 23 |
| 084 | ▼a 006.332 ▼2 DDCK | |
| 090 | ▼a 006.332 | |
| 245 | 0 0 | ▼a Ontology-based data access leveraging subjective reports ▼h [electronic resource] / ▼c Gerardo I. Simari ... [et al.]. |
| 260 | ▼a Cham : ▼b Springer, ▼c c2017. | |
| 300 | ▼a 1 online resource (viii, 77 p.) : ▼b ill. | |
| 490 | 1 | ▼a SpringerBriefs in Computer Science, ▼x 2191-5768 |
| 500 | ▼a Title from e-Book title page. | |
| 504 | ▼a Includes bibliographical references. | |
| 505 | 0 | ▼a 1 Ontology-Based Data Access with Datalog+/- -- 2 Models for Representing User Preferences -- 3 Subjective Data: Model and Query Answering -- 4 Related Research Lines. |
| 520 | ▼a 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 e derived, 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. Since this SpringerBrief contains a gentle introduction to the main building blocks (OBDA, Datalog+/-, and reasoning with preferences), it should be of value to students, researchers, and practitioners who are interested in the general problem of incorporating user preferences into related formalisms and tools. Practitioners also interested in using Ontology-based Data Access to leverage information contained in reviews of products and services for a better customer experience will be interested in this brief and researchers working in the areas of Ontological Languages, Semantic Web, Data Provenance, and Reasoning with Preferences. | |
| 530 | ▼a Issued also as a book. | |
| 538 | ▼a Mode of access: World Wide Web. | |
| 650 | 0 | ▼a Ontologies (Information retrieval). |
| 650 | 0 | ▼a Data mining. |
| 700 | 1 | ▼a Simari, Gerardo I. |
| 830 | 0 | ▼a SpringerBriefs in Computer Science. |
| 856 | 4 0 | ▼u https://oca.korea.ac.kr/link.n2s?url=https://doi.org/10.1007/978-3-319-65229-0 |
| 945 | ▼a KLPA | |
| 991 | ▼a E-Book(소장) |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 중앙도서관/e-Book 컬렉션/ | 청구기호 CR 006.332 | 등록번호 E14015270 | 도서상태 대출불가(열람가능) | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
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
e derived, 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.
Since this SpringerBrief contains a gentle introduction to the main building blocks (OBDA, Datalog+/-, and reasoning with preferences), it should be of value to students, researchers, and practitioners who are interested in the general problem of incorporating user preferences into related formalisms and tools. ?Practitioners also ?interested in using Ontology-based Data Access to leverage information contained in reviews of products and services for a better customer experience will be interested in this brief and ?researchers working in the areas of Ontological Languages, Semantic Web, Data Provenance, and Reasoning with Preferences.
정보제공 :
목차
1 Ontology-Based Data Access with Datalog+/- 2 Models for Representing User Preferences 3 Subjective Data: Model and Query Answering 4 Related Research Lines.