Entity Embeddings Analysis. The results of Table 2 suggest that graph-based entity embeddings yield bet- ter performance compared to context only entity embeddings. To analyze why graph-based entity embeddings are beneficial for entity retrieval models, we con- duct a set of experiments and investigate properties of embeddings with and without the graph structure. According to the cluster hypothesis [14], documents relevant to the same query should cluster together. We consider the embeddings as data-points to be clustered and compare the resulting clusters in several ways. First, we compute the Davies Bouldin index [5] and the Silhouette index [24], which are: 3.16 and
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Samples: End User Agreement, End User Agreement, End User Agreement
Entity Embeddings Analysis. The results of Table 2 suggest that graph-based entity embeddings yield bet- ter performance compared to context only entity embeddings. To analyze why graph-based entity embeddings are beneficial beneficial for entity retrieval models, we con- duct a set of experiments and investigate properties of embeddings with and without the graph structure. According to the cluster hypothesis [14], documents relevant to the same query should cluster together. We consider the embeddings as data-points to be clustered and compare the resulting clusters in several ways. First, we compute the Davies Bouldin index [5] and the Silhouette index [24], which are: 3.16 and
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Samples: End User Agreement