… Extreme multi-label text classification (XMTC) is a task for tagging a given text with the most
relevant labels from an extremely … for the application of extreme multi-label text classification. …

… extreme multi-label text classification (XMC) problem: given an input text, return the most
relevant labels from a large label … On the right is the clusters distribution after our semantic label …

… relevant label clusters (instead of labels themselves). If B ≈ … framework for extreme multi-label
text classification where the … objectives defined by a hierarchical label tree. This allows the …

… Extreme multi-label text classification (XMTC) aims … clusters varying with different label
clustering approaches. 75.8% of the clusters have more than 100 training instances by our label …

… Different from Parabel, we only keep the leaves of this tree as its clustering result. Now we …
label-wise attention network, which can solve extreme multi-label text classification efficiently …

… data into many clusters, and learns embeddings for each separate cluster, then kNN search
is performed only within the cluster this novel document belongs to. Since clustering high di…

… Extreme multi-label text classification (XMTC) is an important … text with the most relevant
multiple labels from an extremely … clusters until the cluster size (the number of labels in each …

… of a Deep Learning architecture devoted to text classification, considering the extreme
multi-class and multi-label text classification problem, when a hierarchical label set is defined. The …

… Extreme multi-label text classification (XMTC) aims at tagging a document with most relevant
labels from an extremely large-scale label set… set into several clusters, and in each cluster it …

… extreme multi-label learning is to train a classifier that can automatically tag a novel data point
with the most relevant subset of labels … To scale our algorithm, we perform a clustering of …