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.+HPLC+combines+landmark+selection+and+graph+clustering%252C+where+the+graph+is+partitioned+into+densely+connected+clusters+in+which+nodes+with+the+highest+degree+are+selected+as+landmarks.+HPLC+leverages+the+positional+information+of+nodes+based+on+landmarks+at+various+levels+of+hierarchy+such+as+nodes%27+distances+to+landmarks%252C+inter-landmark+distances+and+hierarchical+grouping+of+clusters.+Experiments+show+that+HPLC+achieves+state-of-the-art+performances+of+link+prediction+on+various+datasets+in+terms+of+HIT%2540K%252C+MRR%252C+and+AUC.+The+code+is+available+at+url%7bhttps%3a%252F%252Fgithub.com%252Fkmswin1%252FHPLC%7d.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.dd9d30a84d8cb1d799270bab3c5071a0%3frik%3dIC2ZwlbIj%252b8W0g%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=2D+Positional+Map+for+Position+Embedding&FORM=IRPRST&ck=85B131E30EF26DB1A0C3860CE344374D&selectedIndex=10&itb=0)
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