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Summary: Spectral Analysis of Data
Yossi Azar y Amos Fiat y Anna R. Karlin z Frank McSherry z Jared Saia z
Every action must be due to one or other of seven causes:
chance, nature, compulsion, habit, reasoning, anger, or
appetite.
| Aristotle, Rhetoric, Bk. II.
No one wants advice | only corroboration.
| John Steinbeck, The Winter of Our Discontent.
ABSTRACT
Experimental evidence suggests that spectral techniques are
valuable for a wide range of applications. A partial list of
such applications include (i) semantic analysis of documents
used to cluster documents into areas of interest, (ii) collab-
orative ltering | the reconstruction of missing data items,
and (iii) determining the relative importance of documents
based on citation/link structure. Intuitive arguments can
explain some of the phenomena that has been observed but
little theoretical study has been done. In this paper we
present a model for framing data mining tasks and a uni-
ed approach to solving the resulting data mining problems
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