summaryrefslogtreecommitdiff
path: root/macros/latex/contrib/bjfuthesis
diff options
context:
space:
mode:
authorNorbert Preining <norbert@preining.info>2021-07-03 03:00:50 +0000
committerNorbert Preining <norbert@preining.info>2021-07-03 03:00:50 +0000
commit03fa062b03ce2bb5385f8f30888f94d441fa5cb4 (patch)
tree530eb375fdfffeaee8890906d3f42f70eab4753e /macros/latex/contrib/bjfuthesis
parentc4d400d058136a9045857b99d816595e7a655125 (diff)
CTAN sync 202107030300
Diffstat (limited to 'macros/latex/contrib/bjfuthesis')
-rw-r--r--macros/latex/contrib/bjfuthesis/README.md2
-rw-r--r--macros/latex/contrib/bjfuthesis/bjfuthesis.cls2
-rw-r--r--macros/latex/contrib/bjfuthesis/example/thesis.lyx2
-rw-r--r--macros/latex/contrib/bjfuthesis/example/thesis.pdfbin5192032 -> 5192031 bytes
-rw-r--r--macros/latex/contrib/bjfuthesis/example/thesis.tex2
5 files changed, 4 insertions, 4 deletions
diff --git a/macros/latex/contrib/bjfuthesis/README.md b/macros/latex/contrib/bjfuthesis/README.md
index 7f8ce30d44..657d5bd880 100644
--- a/macros/latex/contrib/bjfuthesis/README.md
+++ b/macros/latex/contrib/bjfuthesis/README.md
@@ -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.
diff --git a/macros/latex/contrib/bjfuthesis/bjfuthesis.cls b/macros/latex/contrib/bjfuthesis/bjfuthesis.cls
index 86b1ac4ca9..d9b081d376 100644
--- a/macros/latex/contrib/bjfuthesis/bjfuthesis.cls
+++ b/macros/latex/contrib/bjfuthesis/bjfuthesis.cls
@@ -23,7 +23,7 @@
\def\keywords@label@zh{关键词:}
\def\keywords@label@en{Keywords: }
\def\chartnote@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]
\DeclareOption*{\PassOptionsToClass{\CurrentOption}{ctexbook}}
\ProcessOptions*
\LoadClass[a4paper,oneside,fontset=none]{ctexbook}
diff --git a/macros/latex/contrib/bjfuthesis/example/thesis.lyx b/macros/latex/contrib/bjfuthesis/example/thesis.lyx
index f9e1c29eb7..9c1ba84d64 100644
--- a/macros/latex/contrib/bjfuthesis/example/thesis.lyx
+++ b/macros/latex/contrib/bjfuthesis/example/thesis.lyx
@@ -334,7 +334,7 @@ status collapsed
\end_inset
-Knowledge graph, recommender system, Ripple Network, user preferences, movie
+knowledge graph, recommender system, ripple network, user preferences, movie
store
\begin_inset ERT
status collapsed
diff --git a/macros/latex/contrib/bjfuthesis/example/thesis.pdf b/macros/latex/contrib/bjfuthesis/example/thesis.pdf
index 4cf4a4be59..ab18c71cd8 100644
--- a/macros/latex/contrib/bjfuthesis/example/thesis.pdf
+++ b/macros/latex/contrib/bjfuthesis/example/thesis.pdf
Binary files differ
diff --git a/macros/latex/contrib/bjfuthesis/example/thesis.tex b/macros/latex/contrib/bjfuthesis/example/thesis.tex
index ca60a755e1..6cc0b28e89 100644
--- a/macros/latex/contrib/bjfuthesis/example/thesis.tex
+++ b/macros/latex/contrib/bjfuthesis/example/thesis.tex
@@ -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.
\end{abstract}
-\keywordsen{Knowledge graph, recommender system, Ripple Network, user preferences, movie store}
+\keywordsen{knowledge graph, recommender system, ripple network, user preferences, movie store}
\tableofcontents
\mainmatter
\chapter{绪论}