Mobile intention recognition
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| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Springer
2012
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| Online-Zugang: | Inhaltsverzeichnis |
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MARC
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| 008 | 120111s2012 xx abd| m||| 00||| eng d | ||
| 020 | |a 9781461418535 |c hbk |9 978-1-4614-1853-5 | ||
| 020 | |a 9781461418542 |c ebk |9 978-1-4614-1854-2 | ||
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| 100 | 1 | |a Kiefer, Peter |e Verfasser |0 (DE-588)1018724516 |4 aut | |
| 245 | 1 | 0 | |a Mobile intention recognition |c Peter Kiefer |
| 264 | 1 | |a New York [u.a.] |b Springer |c 2012 | |
| 300 | |a XVI, 166 S. |b Ill., graph. Darst., Kt. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Auch erschienen als kostenpflichtige elektron. Ausg. | ||
| 502 | |a Zugl.: Bamberg, Univ., Diss., 2011 u.d.T.: Kiefer, Peter: The mobile intention recognition problem and an approach based on spatially-constrained grammars | ||
| 650 | 0 | 7 | |a Intention |0 (DE-588)4129755-6 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Erkennung |0 (DE-588)4328500-4 |2 gnd |9 rswk-swf |
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| 689 | 0 | 1 | |a Intention |0 (DE-588)4129755-6 |D s |
| 689 | 0 | 2 | |a Erkennung |0 (DE-588)4328500-4 |D s |
| 689 | 0 | 3 | |a Algorithmus |0 (DE-588)4001183-5 |D s |
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| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |o 10.1007/978-1-4614-1854-2 |
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| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-024658600 | |
Datensatz im Suchindex
| _version_ | 1819589997930479616 |
|---|---|
| adam_text | Contents
Introduction
.............................................. 1
1.1
From Location-Based to Intention-Aware Mobile Services
.... 1
1.1.1
Location-Based Services
........................... 1
1.1.2
The Need for Intention-Awareness
.................. 3
1.1.3
Non-Local Dependencies: The Visit/Revisit Problem
.. 6
1.2
Contributions
.......................................... 7
1.3
Outline
............................................... 8
Mobile Intention Recognition
............................. 11
2.1
Intention-Aware Mobile Services
.......................... 11
2.1.1
The Context-Model of IAMSs
...................... 11
2.1.2
Crossing the Semantic Gap
........................ 14
2.2
Intentions and Intention Recognition
...................... 24
2.2.1
Beliefs, Desires, Intentions, and Plans
............... 24
2.2.2
Intention Recognition and Plan Recognition
......... 28
2.3
The Mobile Intention Recognition Problem
................ 31
2.3.1
Spatio-
Temporal Behavior Sequences
................ 31
2.3.2
Mobile Intention Recognition: A Definition
.......... 38
2.3.3
Behavior Sequence Compositions
................... 41
2.3.4
The Problem of Interleaved Intentions
.............. 47
2.4
Summary and Requirements for Mobile Intention Recognition
52
Related Approaches in Plan Recognition
................. 55
3.1
Finite State Machines
................................... 55
3.2
Early Approaches to Plan Recognition
.................... 57
3.2.1
Hypothesize and Revise
........................... 57
3.2.2
Event Hierarchies
................................ 58
3.3
Probabilistic Networks
.................................. 59
3.3.1
Static Probabilistic Networks
...................... 59
3.3.2
Dynamic Probabilistic Networks
.................... 62
3.4
Parsing Formal Grammars
............................... 65
Contents
3.4.1
(Probabilistic)
Context-Free Parsing
................ 65
3.4.2
Spatially Grounded Intentional Systems
............. 69
3.4.3
Towards More Context-Sensitivity
.................. 72
3.5
Combining Formal Grammars and
Bayes
.................. 73
3.5.1
Probabilistic State-Dependent Grammars
............ 73
3.5.2
Plan Tree Grammars and Pending Sets
.............. 74
3.6
Summary
.............................................. 77
Mobile Intention Recognition with Spatially Constrained
Grammars
................................................ 79
4.1
Parsing Spatial Behavior Sequences
....................... 79
4.1.1
A State Chart Parser for SGISs
.................... 79
4.1.2
Spatial Constraint Resolution
...................... 83
4.2
Non-Local Constraints: A Generalization of Spatial Grounding
88
4.2.1
Spatially-Constrained Context-Free Grammars
....... 88
4.2.2
A State Chart Parser for SCCFGs
.................. 90
4.3
Intersecting Spatial Dependencies
........................ 93
4.3.1
Towards More Context-Sensitivity: A Parallel to NLP
. 93
4.3.2
Spatially Constrained Tree-Adjoining Grammars
..... 97
4.3.3
SCTAGs and the Mobile Intention Recognition ProblemlOl
4.3.4
A State Chart Parser for SCTAGs
..................104
4.4
Beyond Partonomies
....................................124
4.5
Summary
..............................................125
Evaluation and Discussion
................................127
5.1
The Clothes Shop Example
..............................127
5.2
Formalizing the Example with Spatial Grammars
...........129
5.2.1
IS and SGIS
.....................................129
5.2.2
SCCFG
.........................................130
5.2.3
SCTAG
.........................................130
5.3
Results and Discussion
..................................131
5.3.1
Ambiguity Reduction with SGISs
...................131
5.3.2
Ambiguity Reduction with SCCFGs
................134
5.3.3
Avoiding Inconsistency with SCTAGs
...............135
5.4
INTENSIVE: A Simulation and Testing Environment for
the IAMS Framework
...................................137
Conclusion and Outlook
..................................145
6.1
Mobile Intention Recognition
............................145
6.2
Spatially Constrained Grammars
.........................146
6.3
Future Research
........................................149
6.3.1
Temporal Constraints
.............................149
6.3.2
Look-Ahead Parsing
..............................151
6.3.3
Probabilistic Spatially Constrained Grammars
.......151
6.3.4
Grammar Acquisition and Behavioral Corpora
.......152
Contents xiii
6.3.5
Multi-
Agent Intention
Recognition..................
153
References
....................................................155
|
| any_adam_object | 1 |
| author | Kiefer, Peter |
| author_GND | (DE-588)1018724516 |
| author_facet | Kiefer, Peter |
| author_role | aut |
| author_sort | Kiefer, Peter |
| author_variant | p k pk |
| building | Verbundindex |
| bvnumber | BV039798076 |
| classification_rvk | ST 302 |
| ctrlnum | (OCoLC)775083863 (DE-599)BVBBV039798076 |
| discipline | Informatik |
| format | Thesis Book |
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| genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV039798076 |
| illustrated | Illustrated |
| indexdate | 2024-12-24T02:30:20Z |
| institution | BVB |
| isbn | 9781461418535 9781461418542 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-024658600 |
| oclc_num | 775083863 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-521 |
| owner_facet | DE-473 DE-BY-UBG DE-521 |
| physical | XVI, 166 S. Ill., graph. Darst., Kt. |
| publishDate | 2012 |
| publishDateSearch | 2012 |
| publishDateSort | 2012 |
| publisher | Springer |
| record_format | marc |
| spellingShingle | Kiefer, Peter Mobile intention recognition Intention (DE-588)4129755-6 gnd Erkennung (DE-588)4328500-4 gnd Mobile Telekommunikation (DE-588)4341131-9 gnd Algorithmus (DE-588)4001183-5 gnd |
| subject_GND | (DE-588)4129755-6 (DE-588)4328500-4 (DE-588)4341131-9 (DE-588)4001183-5 (DE-588)4113937-9 |
| title | Mobile intention recognition |
| title_auth | Mobile intention recognition |
| title_exact_search | Mobile intention recognition |
| title_full | Mobile intention recognition Peter Kiefer |
| title_fullStr | Mobile intention recognition Peter Kiefer |
| title_full_unstemmed | Mobile intention recognition Peter Kiefer |
| title_short | Mobile intention recognition |
| title_sort | mobile intention recognition |
| topic | Intention (DE-588)4129755-6 gnd Erkennung (DE-588)4328500-4 gnd Mobile Telekommunikation (DE-588)4341131-9 gnd Algorithmus (DE-588)4001183-5 gnd |
| topic_facet | Intention Erkennung Mobile Telekommunikation Algorithmus Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024658600&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT kieferpeter mobileintentionrecognition |