| 000 | 05504nam a2200721 i 4500 | ||
|---|---|---|---|
| 001 | 8950308 | ||
| 003 | IEEE | ||
| 005 | 20200413152934.0 | ||
| 006 | m eo d | ||
| 007 | cr bn |||m|||a | ||
| 008 | 200126s2020 paua ob 000 0 eng d | ||
| 020 |
_a9781681737201 _qelectronic |
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| 020 |
_a9781681737645 _qepub |
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| 020 |
_z9781681737218 _qhardcover |
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| 020 |
_z9781681737195 _qpaperback |
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| 024 | 7 |
_a10.2200/S00965ED1V01Y201911MPC014 _2doi |
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| 035 | _a(CaBNVSL)thg00980003 | ||
| 035 | _a(OCoLC)1135668765 | ||
| 040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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| 050 | 4 |
_aQA76.54 _b.M455 2020eb |
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| 082 | 0 | 4 |
_a004/.33 _223 |
| 100 | 1 |
_aMehrotra, Abhinav, _eauthor. |
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| 245 | 1 | 0 |
_aIntelligent notification systems / _cAbhinav Mehrotra, Mirco Musolesi. |
| 264 | 1 |
_a[San Rafael, California] : _bMorgan & Claypool, _c[2020] |
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| 300 |
_a1 PDF (xiii, 61 pages) : _billustrations. |
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| 336 |
_atext _2rdacontent |
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| 337 |
_aelectronic _2isbdmedia |
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| 338 |
_aonline resource _2rdacarrier |
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| 490 | 1 |
_aSynthesis lectures on mobile and pervasive computing, _x1933-902X ; _v#14 |
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| 538 | _aMode of access: World Wide Web. | ||
| 538 | _aSystem requirements: Adobe Acrobat Reader. | ||
| 500 | _aPart of: Synthesis digital library of engineering and computer science. | ||
| 504 | _aIncludes bibliographical references (pages 51-60). | ||
| 505 | 0 | _a1. Introduction -- 1.1. Mobile notifications -- 1.2. Issues with mobile notifications -- 1.3. Solutions for interruptibility management | |
| 505 | 8 | _a2. Interruptions -- 2.1. Definitions of interruptions from different research fields -- 2.2. Types of interruptions -- 2.3. Definition of interruptions in context of this lecture -- 2.4. Sources of interruptions | |
| 505 | 8 | _a3. Cost of interruption -- 3.1. Impact on memory -- 3.2. Impact on ongoing task performance -- 3.3. Impact on users' emotional state -- 3.4. Impact on user experience -- 3.5. Individual differences in perceiving disruption from interruptions -- 3.6. Summary | |
| 505 | 8 | _a4. An Overview of interruptibility management -- 4.1. Definition -- 4.2. Key dimensions for the design of interruptibility management systems | |
| 505 | 8 | _a5. Interruptibility management in desktop environments -- 5.1. Interruptibility management by exploiting task-related information -- 5.2. Interruptibility management by using contextual data -- 5.3. Summary | |
| 505 | 8 | _a6. Interruptibility management in mobile environments -- 6.1. Understanding users' perception toward interruptions caused by mobile notifications -- 6.2. Designing interruptibility management systems for delivering the right information at the right time -- 6.3. Designing interruptibility management systems for multi-device environments -- 6.4. Interruptibility management--an alternative approach for context-aware assistive apps -- 6.5. Summary | |
| 505 | 8 | _a7. Limitations of the state of the art and open challenges -- 7.1. Deferring notifications -- 7.2. Monitoring cognitive context -- 7.3. Learning "good" behavior : interruptions for positive behavior intervention -- 7.4. Modeling for multiple devices -- 7.5. Need for large-scale studies -- 8. Summary. | |
| 506 | _aAbstract freely available; full-text restricted to subscribers or individual document purchasers. | ||
| 510 | 0 | _aCompendex | |
| 510 | 0 | _aINSPEC | |
| 510 | 0 | _aGoogle scholar | |
| 510 | 0 | _aGoogle book search | |
| 520 | _aNotifications provide a unique mechanism for increasing the effectiveness of real-time information delivery systems. However, notifications that demand users' attention at inopportune moments are more likely to have adverse effects and might become a cause of potential disruption rather than proving beneficial to users. In order to address these challenges a variety of intelligent notification mechanisms based on monitoring and learning users' behavior have been proposed. The goal of such mechanisms is maximizing users' receptivity to the delivered information by automatically inferring the right time and the right context for sending a certain type of information. This book presents an overview of the current state of the art in the area of intelligent notification mechanisms that rely on the awareness of users' context and preferences. We first present a survey of studies focusing on understanding and modeling users' interruptibility and receptivity to notifications from desktops and mobile devices. Then, we discuss the existing challenges and opportunities in developing mechanisms for intelligent notification systems in a variety of application scenarios. | ||
| 530 | _aAlso available in print. | ||
| 588 | _aTitle from PDF title page (viewed on January 26, 2020). | ||
| 650 | 0 | _aReal-time data processing. | |
| 650 | 0 | _aData transmission systems. | |
| 653 | _anotification systems | ||
| 653 | _ainterruptibility | ||
| 653 | _acontext-aware computing | ||
| 653 | _aanticipatory computing | ||
| 653 | _aintelligent mobile systems | ||
| 653 | _aintelligent user interfaces | ||
| 700 | 1 |
_aMusolesi, Mirco, _eauthor. |
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| 776 | 0 | 8 |
_iPrint version: _z _z9781681737218 _z9781681737195 |
| 830 | 0 | _aSynthesis digital library of engineering and computer science. | |
| 830 | 0 |
_aSynthesis lectures on mobile and pervasive computing ; _v#14. |
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| 856 | 4 | 2 |
_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/servlet/opac?bknumber=8950308 |
| 856 | 4 | 0 |
_3Abstract with links to full text _uhttps://doi.org/10.2200/S00965ED1V01Y201911MPC014 |
| 999 |
_c562457 _d562457 |
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