Results 31 to 40 of about 3,366,127 (326)
When are the natural embeddings of classical invariant rings pure?
Forum of Mathematics, Sigma, 2023 Consider a reductive linear algebraic group G acting linearly on a polynomial ring S over an infinite field; key examples are the general linear group, the symplectic group, the orthogonal group, and the special linear group, with the classical ...
Melvin Hochster +3 more
doaj +1 more source
Multitask feature learning approach for knowledge graph enhanced recommendations with RippleNet.
PLoS ONE, 2021 Introducing a knowledge graph into a recommender system as auxiliary information can effectively solve the sparse and cold start problems existing in traditional recommender systems. In recent years, many researchers have performed related work.
YueQun Wang +3 more
doaj +1 more source
Two-Terminal Neighbor Information Fusion Recommendation Algorithm Based on Knowledge Graph [PDF]
Jisuanji kexue yu tansuo, 2022 In view of the problem that some recommendation algorithms based on knowledge graphs only aggregate one end of the neighbors and cannot effectively determine the relationship between entities and users, this paper proposes a dual-end neighbor aggregation
WANG Baoliang, PAN Wencai
doaj +1 more source
Semantic Dependency Parsing via Book Embedding
Annual Meeting of the Association for Computational Linguistics, 2017 We model a dependency graph as a book, a particular kind of topological space, for semantic dependency parsing. The spine of the book is made up of a sequence of words, and each page contains a subset of noncrossing arcs.
Weiwei SUN, Junjie Cao, Xiaojun Wan
semanticscholar +1 more source
On the Genus of the Idempotent Graph of a Finite Commutative Ring
Discussiones Mathematicae - General Algebra and Applications, 2021 Let R be a finite commutative ring with identity. The idempotent graph of R is the simple undirected graph I(R) with vertex set, the set of all nontrivial idempotents of R and two distinct vertices x and y are adjacent if and only if xy = 0.
Belsi G. Gold, Kavitha S., Selvakumar K.
doaj +1 more source
Feature Extracted Deep Neural Collaborative Filtering for E-Book Service Recommendations
Applied Sciences, 2023 The electronic publication market is growing along with the electronic commerce market. Electronic publishing companies use recommendation systems to increase sales to recommend various services to consumers.
Ji-Yoon Kim, Chae-Kwan Lim
doaj +1 more source
Ri-vista: Ricerche per la Progettazione del Paesaggio, 2015 The book - catalog Paesaggi agrari. L'irrinunciabile eredità scientifica di Emilio Sereni edith by Massimo Quaini in collaboration with Gabriella Bonini, Claudio Cerreti, Luisa Rossi and Chiara Visentin - acknowledges and deepens into ten chapters the ...
Gabriella Bonini
doaj +1 more source
IEEE Access, 2023 Enterprise Architecture (EA) is crucial in any organisation as it defines the basic building blocks of a business. It is typically presented as a set of documents that help all departments understand the business model.
Abdul Wahab Qurashi +3 more
doaj +1 more source
Slavica Revalensia, 2019 The article discusses the possibility of classifying poetic books on the basis of their vocabulary. The distance between 190 poem collections is calculated as the Euclidean distance between books’ vocabularies, for each element of which the value of TF ...
Boris Orekhov
doaj +1 more source
The Use of Attentive Knowledge Graph Perceptual Propagation for Improving Recommendations
Applied Sciences, 2023 Collaborative filtering (CF) usually suffers from data sparsity and cold starts. Knowledge graphs (KGs) are widely used to improve recommendation performance.
Chenming Wang, Bo Huang
doaj +1 more source