Research Article
Context Attention Heterogeneous Network Embedding
| % training edges | 15% | 25% | 35% | 45% | 55% | 65% | 75% | 85% | 95% |
| DeepWalk | 0.469 | 0.472 | 0.497 | 0.507 | 0.533 | 0.537 | 0.556 | 0.574 | 0.587 | LINE | 0.521 | 0.569 | 0.618 | 0.624 | 0.655 | 0.636 | 0.646 | 0.676 | 0.698 | Node2vec | 0.488 | 0.482 | 0.507 | 0.505 | 0.552 | 0.546 | 0.558 | 0.582 | 0.590 | GraRep | 0.583 | 0.619 | 0.642 | 0.659 | 0.654 | 0.662 | 0.663 | 0.668 | 0.663 | Naive Combination | 0.524 | 0.553 | 0.579 | 0.618 | 0.653 | 0.672 | 0.689 | 0.705 | 0.703 | TADW | 0.558 | 0.576 | 0.593 | 0.625 | 0.655 | 0.697 | 0.696 | 0.723 | 0.729 | TENE | 0.551 | 0.549 | 0.607 | 0.622 | 0.660 | 0.666 | 0.668 | 0.692 | 0.711 | ASNE | 0.586 | 0.563 | 0.608 | 0.633 | 0.661 | 0.682 | 0.699 | 0.700 | 0.728 | CAHNE(w/o context) | 0.595 | 0.600 | 0.603 | 0.604 | 0.612 | 0.618 | 0.639 | 0.657 | 0.679 | CAHNE | 0.623 | 0.693 | 0.706 | 0.709 | 0.707 | 0.711 | 0.713 | 0.722 | 0.731 | CAHNE-a | 0.631 | 0.707 | 0.721 | 0.724 | 0.723 | 0.727 | 0.736 | 0.748 | 0.759 |
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