語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Bridging Levels of Analysis : = Lear...
~
ProQuest Information and Learning Co.
Bridging Levels of Analysis : = Learning, Information Theory, and the Lexicon.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Bridging Levels of Analysis :/
其他題名:
Learning, Information Theory, and the Lexicon.
作者:
Dye, Melody.
面頁冊數:
1 online resource (190 pages)
附註:
Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
標題:
Cognitive psychology. -
電子資源:
click for full text (PQDT)
ISBN:
9780355223644
Bridging Levels of Analysis : = Learning, Information Theory, and the Lexicon.
Dye, Melody.
Bridging Levels of Analysis :
Learning, Information Theory, and the Lexicon. - 1 online resource (190 pages)
Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
Thesis (Ph.D.)--Indiana University, 2017.
Includes bibliographical references
While information theory is typically considered in the context of modern computing and engineering, its core mathematical principles provide a potentially useful lens through which to consider human language. Like the artificial communication systems such principles were invented to describe, natural languages involve a sender and receiver, a finite code, and a basic transmission problem. Human languages can thus be seen as socially evolved systems that have been structured to optimize information flow in communication. Over the past several decades, information theoretic approaches have attracted widespread interest among linguists and psychologists, and generated a productive research program focused on cataloging how speakers (in their utterances) and languages (in their design) conform to its principles. However, comparatively little work has been done to explicate how the cognitive mechanisms that subserve language give rise to such apparently rational behavior. Showing why speakers conform to such principles is an important correlate to showing that they do. A communication system, no matter how efficiently coded, must also be possible for humans to learn and to use. In this dissertation, I adopt an information theoretic approach to elucidating the challenges posed by the construction and maintenance of a workable lexicon, with the express aim of bridging the gap between rational and mechanistic accounts. To this end, I detail a series of large-scale corpus analyses and behavioral experiments that investigate (1) how languages (and linguistic sub-systems) solve the problem of assigning names to things, (2) how principles of learning and memory act to constrain the possible solution space, and (3) how different solutions present trade-offs for learnability and efficient processing. These investigations shed light on a few of the methods natural languages use to solve a complex constraint-satisfaction problem.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355223644Subjects--Topical Terms:
556029
Cognitive psychology.
Index Terms--Genre/Form:
554714
Electronic books.
Bridging Levels of Analysis : = Learning, Information Theory, and the Lexicon.
LDR
:03148ntm a2200337K 4500
001
913850
005
20180628103545.5
006
m o u
007
cr mn||||a|a||
008
190606s2017 xx obm 000 0 eng d
020
$a
9780355223644
035
$a
(MiAaPQ)AAI10621811
035
$a
(MiAaPQ)indiana:14906
035
$a
AAI10621811
040
$a
MiAaPQ
$b
eng
$c
MiAaPQ
100
1
$a
Dye, Melody.
$3
1186856
245
1 0
$a
Bridging Levels of Analysis :
$b
Learning, Information Theory, and the Lexicon.
264
0
$c
2017
300
$a
1 online resource (190 pages)
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
500
$a
Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
500
$a
Advisers: Michael N. Jones; Richard Shiffrin.
502
$a
Thesis (Ph.D.)--Indiana University, 2017.
504
$a
Includes bibliographical references
520
$a
While information theory is typically considered in the context of modern computing and engineering, its core mathematical principles provide a potentially useful lens through which to consider human language. Like the artificial communication systems such principles were invented to describe, natural languages involve a sender and receiver, a finite code, and a basic transmission problem. Human languages can thus be seen as socially evolved systems that have been structured to optimize information flow in communication. Over the past several decades, information theoretic approaches have attracted widespread interest among linguists and psychologists, and generated a productive research program focused on cataloging how speakers (in their utterances) and languages (in their design) conform to its principles. However, comparatively little work has been done to explicate how the cognitive mechanisms that subserve language give rise to such apparently rational behavior. Showing why speakers conform to such principles is an important correlate to showing that they do. A communication system, no matter how efficiently coded, must also be possible for humans to learn and to use. In this dissertation, I adopt an information theoretic approach to elucidating the challenges posed by the construction and maintenance of a workable lexicon, with the express aim of bridging the gap between rational and mechanistic accounts. To this end, I detail a series of large-scale corpus analyses and behavioral experiments that investigate (1) how languages (and linguistic sub-systems) solve the problem of assigning names to things, (2) how principles of learning and memory act to constrain the possible solution space, and (3) how different solutions present trade-offs for learnability and efficient processing. These investigations shed light on a few of the methods natural languages use to solve a complex constraint-satisfaction problem.
533
$a
Electronic reproduction.
$b
Ann Arbor, Mich. :
$c
ProQuest,
$d
2018
538
$a
Mode of access: World Wide Web
650
4
$a
Cognitive psychology.
$3
556029
650
4
$a
Linguistics.
$3
557829
650
4
$a
Information science.
$3
561178
655
7
$a
Electronic books.
$2
local
$3
554714
690
$a
0633
690
$a
0290
690
$a
0723
710
2
$a
ProQuest Information and Learning Co.
$3
1178819
710
2
$a
Indiana University.
$b
Cognitive Science.
$3
1186575
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10621811
$z
click for full text (PQDT)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入