texlive[59809] Master/texmf-dist: bjfuthesis (2jul21)

commits+karl at tug.org commits+karl at tug.org
Fri Jul 2 21:57:44 CEST 2021

Revision: 59809
Author:   karl
Date:     2021-07-02 21:57:44 +0200 (Fri, 02 Jul 2021)
Log Message:
bjfuthesis (2jul21)

Modified Paths:

Modified: trunk/Master/texmf-dist/doc/latex/bjfuthesis/README.md
--- trunk/Master/texmf-dist/doc/latex/bjfuthesis/README.md	2021-07-02 11:24:27 UTC (rev 59808)
+++ trunk/Master/texmf-dist/doc/latex/bjfuthesis/README.md	2021-07-02 19:57:44 UTC (rev 59809)
@@ -1,7 +1,7 @@
 # 北京林业大学 (BJFU) 毕业论文模板 (LaTeX)
 Copyright (C) 2021 Liu Changxin
-Version 1.2.0 (2021-06-21)
+Version 1.2.1 (2021-07-01)
 ## Abstract
 This is a class file for producing dissertations and theses according to the Beijing Forestry University (BJFU) Guidelines for Undergraduate Theses and Dissertations.

Modified: trunk/Master/texmf-dist/doc/latex/bjfuthesis/example/thesis.lyx
--- trunk/Master/texmf-dist/doc/latex/bjfuthesis/example/thesis.lyx	2021-07-02 11:24:27 UTC (rev 59808)
+++ trunk/Master/texmf-dist/doc/latex/bjfuthesis/example/thesis.lyx	2021-07-02 19:57:44 UTC (rev 59809)
@@ -334,7 +334,7 @@
-Knowledge graph, recommender system, Ripple Network, user preferences, movie
+knowledge graph, recommender system, ripple network, user preferences, movie
 \begin_inset ERT
 status collapsed

Modified: trunk/Master/texmf-dist/doc/latex/bjfuthesis/example/thesis.pdf
(Binary files differ)

Modified: trunk/Master/texmf-dist/doc/latex/bjfuthesis/example/thesis.tex
--- trunk/Master/texmf-dist/doc/latex/bjfuthesis/example/thesis.tex	2021-07-02 11:24:27 UTC (rev 59808)
+++ trunk/Master/texmf-dist/doc/latex/bjfuthesis/example/thesis.tex	2021-07-02 19:57:44 UTC (rev 59809)
@@ -19,7 +19,7 @@
 	This paper implements a recommendation algorithm, ``Ripple Network", based on knowledge graph. The core of the Ripple Network algorithm is to use the idea that the ripples produced by raindrops in real life continue to spread on the water surface to stimulate the spread of user preferences. For each user, Ripple Network uses its past preference as a seed set in the knowledge graph, and then continuously expands the user's preferences along the relationship path in the knowledge graph, and then discovers his hierarchical potential interests concerning a certain candidate item. Multiple ``ripples'' overlap to form the user preference distribution in the knowledge graph. Compared with previous model results of CKE, DKN, PER, etc., the experimental results of this algorithm show better performance. Using this algorithm, this paper designs and implements a recommendation system based on the movie knowledge graph. The system includes administrator users and general users. The administrator can add, edit and delete movies and users, and general users can browse, collect and purchase films. The system can provide users with an efficient movie recommendation function, which is convenient for users to choose movies that match their preferences.
-\keywordsen{Knowledge graph, recommender system, Ripple Network, user preferences, movie store}
+\keywordsen{knowledge graph, recommender system, ripple network, user preferences, movie store}

Modified: trunk/Master/texmf-dist/tex/latex/bjfuthesis/bjfuthesis.cls
--- trunk/Master/texmf-dist/tex/latex/bjfuthesis/bjfuthesis.cls	2021-07-02 11:24:27 UTC (rev 59808)
+++ trunk/Master/texmf-dist/tex/latex/bjfuthesis/bjfuthesis.cls	2021-07-02 19:57:44 UTC (rev 59809)
@@ -23,7 +23,7 @@
 \def\keywords at label@zh{关键词:}
 \def\keywords at label@en{Keywords: }
 \def\chartnote at label{注:}
-\ProvidesClass{bjfuthesis}[2021/06/21 A thesis class for Beijing Forestry University]
+\ProvidesClass{bjfuthesis}[2021/07/01 A thesis class for Beijing Forestry University]

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