In this paper, KGEs are reconciled with a specific loss function (Soft Margin) and examined with respect to their performance for co-authorship link prediction task on scholarly KGs. The results show a significant improvement in the accuracy of the experimented KGE models on the considered ...
论文主要考虑过去的TKGC(Temporal KG Completion)模型学习模式的三个问题: 1、之前的方法并没有显式地将TKGC构造为一种增量学习问题——使模型能够适应训练数据的变化并能有效保留之前所学。它们将TKGC任务简单构造成KGC任务,仅仅在新的KG快照上对模型进行微调,导致灾难性遗忘。这点我不能苟同,既然在新的时间步下...
1 引出# 论文主要考虑过去的TKGC(Temporal KG Completion)模型学习模式的三个问题: 1、之前的方法并没有显式地将TKGC构造为一种增量学习问题——使模型能够适应训练数据的变化并能有效保留之前所学。它们将TKGC任务简单构造成KGC任务,仅仅在新的KG快照上对模型进行微调,导致灾难性遗忘。这点我不能苟同,既然在新...
We generate two versions of datasets for each pair of KGs to be aligned. V1 is generated by directly using the IDS algorithm. For V2, we first randomly delete entities with low degrees (d <= 5) in the source KG to make the average degree doubled, and then execute IDS to fit the ...
论文主要考虑过去的TKGC(Temporal KG Completion)模型学习模式的三个问题: 1、之前的方法并没有显式地将TKGC构造为一种增量学习问题——使模型能够适应训练数据的变化并能有效保留之前所学。它们将TKGC任务简单构造成KGC任务,仅仅在新的KG快照上对模型进行微调,导致灾难性遗忘。这点我不能苟同,既然在新的时间步下...
3 KNOWLEDGE EMBEDDING BASED QA-KG KEQA通过三步完成目标:1)基于 Q 中的问题和他们的谓词的嵌入表示,KEQA训练一个谓词学习模型,其将一个问题作为输入并且返回一个在KG嵌入空间的 \hat{p}_{l} 作为预测谓词表示。相似的,头实体也能被构建为 \hat{e}_{h} 2)因为实体的数量非常多,KEQA使用一个Head Entity...
下载网址:https://www.dropbox.com/s/o5hd8lnr5c0l6hj/KGembed.zip。 里面的 entities_emb.bin, predicates_emb.bin是我们需要学习的嵌入空间 Predicate and Head Entity Learning Models 这是模型双向LSTM和Attention , LSTM 是为了考虑一个question中词的顺序,Attention考虑了每个词对于理解这个问题的重要程度不...
industry.zip |__ attr_triples_1 # attribute triples of KG1 |__ attr_triples_2 # attribute triples of KG2 |__ ent_links # entity links between KGs (ground-truth) |__ rel_triples_1 # relation triples of KG1 |__ rel_triples_2 # relation triples of KG2 ...
专利名称：KNOWLEDGE-GRAPH-EMBEDDING-BASED QUESTION ANSWERING 发明人：Jingyuan ZHANG,Dingcheng LI,Ping LI,Xiao HUANG 申请号：US16262618 申请日：20190130 公开号：US20200242444A1 公开日：20200730 专利内容由知识产权出版社提供 专利附图：摘要：Described herein are embodiments for question answering over ...
Each edge with two nodes in a KG represents a triple of the form (subject, predicate, object), which means the subject and the object are linked by the predicate, e.g., (Bill Clinton, wasBornIn, Arkansas). KGs are widely used and play a crucial role in many fields, such as ...