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 ...
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...
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...
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 ...
标准TKGC评价指标就是用Hits@k等,在某个KG快照上进行,如论文式 (3)。 而增量TKGC的评价指标需要评估两个方面: 1、Current and Historical Average Measure:也就是计算从$1$到$t$的所有时间步增量学习后的标准测试结果的平均。 2、Intransigence Measure:评估模型对已删除事实的识别能力。提出Deleted Facts Hits...
由于机器难以捕获自然语言中的语义信息,QA-KG是一个困难的问题。同时,许多知识图谱嵌入方法被提出了。其核心思想是将每个谓词、实体表示为低维向量,那么在KG中的关系信息能被保留下来。这些学习到的低维向量能被KGC和推荐系统等使用。在本文中,我们使用其来解决QA-KG问题。然后,仍然有一个问题就是一个谓词在自然...
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...
1c, we display the node and edge types of the KGCOVID19 graph and whether sampled edges exist by using the first two components of the t-SNE decomposition of the node/edge embeddings49. Node-label, edge-label, and edge prediction models GRAPE provides implementations to perform node-label ...
usage: python -m cli.main.py [-h] [-t TARGET_ENTITIES] [-kg KG] [-o OUTPUT_FOLDER] [-steps] [-itrs MAX_ITERATIONS] [-e EMBEDDING_DIR] [-Skg] [-en ENCODING_DICT_DIR] [-ed EMBEDDING_ADAPTER] [-em EMBEDDING_METHOD] [-host HOST] [-index INDEX] [-index_d] [-id KG_IDENTIFI...
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 ...