가야대학교 분성도서관

상단 글로벌/추가 메뉴

회원 로그인

주메뉴

: • 전체검색; • 단행본; • 정기간행물; • 학위논문; • 비도서; • 특정번호 검색; • 기사색인; • 학습연구지원; • 지정도서

: • 전자자원통합검색; • 해외 WEB DB; • E-Book; • E-Learning; • 국내 WEB DB; • 인터넷검색

: • 대출현황조회/연장; • 예약현황조회/취소; • 희망도서; • 내서재; • 나의서평; • 나의태그; • 나의위젯; • RSS; • SDI; • 개인정보관리

: • 공지사항; • FAQ; • Q&A 일반·학술; • 신착/인기 도서; • 학위논문온라인제출; • 외부인 이용안내; • 설문조사

: • 도서관 소개; • 연혁; • 현황; • 이용안내; • 찾아오시는 길

자료검색

Home
상세정보

상세정보

검색결과 돌아가기

부가기능

MARC보기

Machine-Learned Ranking Algorithms for E-commerce Search and Recommendation Applications

상세 프로파일

상세정보
자료유형	E-Book
개인저자	Goswami, Anjan.
단체저자명	University of California, Davis. Computer Science.
서명/저자사항	Machine-Learned Ranking Algorithms for E-commerce Search and Recommendation Applications.
발행사항	[S.l.] : University of California, Davis., 2018
발행사항	Ann Arbor : ProQuest Dissertations & Theses, 2018
형태사항	188 p.
소장본 주기	School code: 0029.
ISBN	9780438289369
일반주기	Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. Advisers: Prasant Mohapatra
요약	Search is one of the most critical functionalities of an e-commerce site. Almost every e-commerce site provides a search box. A customer expresses her intent about a product or a category of products in the form of one or more keywords and enter
요약	We begin with the aspect of the evaluation of the ranking algorithms for an e-commerce search and provide guidelines for conducting online randomized controlled experiments on a large e-commerce site. In this regard, we discuss managing biases,
요약	Second, we define a formal framework for designing learning to rank (LTR) algorithms for e-commerce search optimizing the ranking for relevance, revenue, and discovery. We define a measure for discovery and describe the importance of that for an
요약	Third, we address the problem of incorporating diversity in e-commerce search. We design a knapsack based semi-bandit optimization algorithm for simultaneously learning to diversify and maximizing the revenue. We show that the regret of the algo
요약	Fourth, we address the problem of multi-objective learning to rank. We use the LambdaMart algorithm to realize our multi-objective algorithms. LambdaMart algorithm is widely used in Industry, won some recent "learning to rank" challenges. The au
요약	Fifth, we address the problem of quantification and visualization of the excess supply and unmet demand using the contents of the queries and items. We show the impact of such content gap in search experience. We quantify the content gap definin
일반주제명	Computer science.
언어	영어
기본자료 저록	Dissertation Abstracts International79-12B(E). Dissertation Abstract International
대출바로가기	http://www.riss.kr/pdu/ddodLink.do?id=T14997054