Latent Semantic Mapping: Principles & Applications

Front Cover
Morgan & Claypool Publishers, 2007 - Technology & Engineering - 101 pages
0 Reviews
Latent semantic mapping (LSM) is a generalization of latent semantic analysis (LSA), a paradigm originally developed to capture hidden word patterns in a text document corpus. In information retrieval, LSA enables retrieval on the basis of conceptual content, instead of merely matching words between queries and documents. It operates under the assumption that there is some latent semantic structure in the data, which is partially obscured by the randomness of word choice with respect to retrieval. Algebraic and/or statistical techniques are brought to bear to estimate this structure and get rid of the obscuring noise. This results in a parsimonious continuous parameter description of words and documents, which then replaces the original parameterization in indexing and retrieval. This approach exhibits three main characteristics: Discrete entities (words and documents) are mapped onto a continuous vector space; this mapping is determined by global correlation patterns; and dimensionality reduction is an integral part of the process. Such fairly generic properties are advantageous in a variety of different contexts, which motivates a broader interpretation of the underlying paradigm. The outcome (LSM) is a data-driven framework for modeling meaningful global relationships implicit in large volumes of (not necessarily textual) data. This monograph gives a general overview of the framework, and underscores the multifaceted benefits it can bring to a number of problems in natural language understanding and spoken language processing. It concludes with a discussion of the inherent tradeoffs associated with the approach, and some perspectives on its general applicability to data-driven information extraction.
 

What people are saying - Write a review

We haven't found any reviews in the usual places.

Contents

II
3
V
4
VI
7
VIII
8
X
9
XI
10
XIII
11
XV
15
XLIX
50
LI
51
LII
52
LIV
53
LVI
54
LVII
55
LVIII
56
LIX
57

XVI
16
XVIII
17
XIX
18
XX
21
XXI
22
XXIII
23
XXV
24
XXVI
25
XXVII
26
XXVIII
27
XXX
29
XXXI
31
XXXII
33
XXXVI
34
XXXVIII
35
XXXIX
38
XL
41
XLI
42
XLII
43
XLV
44
XLVI
49
LX
58
LXII
59
LXIII
63
LXVI
64
LXVIII
65
LXIX
67
LXX
71
LXXI
72
LXXIII
73
LXXIV
74
LXXV
75
LXXVI
77
LXXVII
79
LXXVIII
80
LXXIX
81
LXXXII
82
LXXXIII
85
LXXXIV
86
LXXXV
89
LXXXVI
101
Copyright

Other editions - View all

Common terms and phrases

Popular passages

Page 93 - S. Deerwester, ST Dumais, GW Furnas, TK Landauer, and R. Harshman. Indexing by latent semantic analysis.
Page 3 - ... to overcome a fundamental problem that plagues existing retrieval techniques that try to match words of queries with words of documents. The problem is that users want to retrieve on the basis of conceptual content, while individual words provide unreliable evidence about the conceptual meaning of a document.
Page 3 - LSA paradigm operates under the assumption that there is some underlying latent semantic structure in the data, which is partially obscured by the randomness of word choice with respect to retrieval. Algebraic and/or statistical techniques are brought to bear to estimate this latent structure and get rid of the obscuring "noise.

Bibliographic information