Towards Comment-based Cross-Media Retrieval

This paper investigates whether Web comments can be exploited for cross-media retrieval. Comparing Web items such as texts, im-ages, videos, music, products, or personal profiles can be done at various levels of detail; our focus is on topic similarity. We propose to compare user-supplied comments on Web items in lieu of the commented items themselves. If this approach is feasible, the task of extracting and mapping features between arbitrary pairs of item types can be circumvented, and well-known text retrieval models can be applied instead—given that comments are available. We re-port on results of a preliminary, but nonetheless large-scale experi-ment which shows that, if comments on textual items are compared with comments on video items, topically similar pairs achieve a sufficiently high cross-media similarity