This ground-breaking text/reference diverges from the normal view that laptop imaginative and prescient (for photograph research) and string processing (for textual content mining) are separate and unrelated fields of analysis, propounding that pictures and textual content might be handled in an identical demeanour for the needs of knowledge retrieval, extraction and category. Highlighting some great benefits of wisdom move among the 2 disciplines, the textual content offers more than a few novel similarity-based studying (SBL) thoughts based in this technique. subject matters and lines: describes various SBL ways, together with nearest neighbor types, neighborhood studying, kernel tools, and clustering algorithms; offers a nearest neighbor version in response to a unique dissimilarity for pictures; discusses a singular kernel for (visual) notice histograms, in addition to a number of kernels in accordance with a pyramid illustration; introduces an strategy according to string kernels for local language id; comprises hyperlinks for downloading suitable open resource code.

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