Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

Language: English

You searched for subject:(and their operations are coordinated to deliver services cooperatively via a sequence of device actions called a plan Due to personalization AND automation). Showing records 1 – 3 of 3 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters

1. Tay, Noel Nuo Wi. Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化.

Degree: 博士(工学), 2017, Tokyo Metropolitan University / 首都大学東京

首都大学東京, 2017-03-25, 博士(工学)

Subjects/Keywords: Smart home consists of various kinds of Internet of Tings (IoT) devices connected to the private house that cooperatively provide inhabitants (users) with proactive services related to comfort; security and safety. Examples of services include 1) manipulation of lighting and temperature based on time and context; 2) reminder service of user’s schedules by using the nearest output device; and 3) device organization to realize surveillance system. However; current smart homes are developed mostly from the viewpoint of technical capabilities; where users have to decide how the connected devices are going to serve them. They may have to setup the devices based on the available functionalities and specifications of the devices; and also have to alter their living styles according to the role of each device. Besides; most devices can only provide simple services independently. Œus; cooperation among the devices is important. On the other hand; human-centric approach; which centered on humans’ need to enhance their living experience; is an important technological paradigm where services are provided anywhere and anytime based on situation. Smart home abiding this approach should cooperatively maximize fulfillment of quality of life (QOL) for individual users subject to personal constraints. In this respect; the devices are bound to enable communication of information; and their operations are coordinated to deliver services cooperatively via a sequence of device actions called a plan. Due to personalization and automation; a number of problems have to be solved. First; a means of automatic binding between loosely coupled devices depending on services delivered have to be devised; as manual setup is impractical. Secondly; coordination of devices needs to generate complex plans; without requiring manual specification of sub-plans. Besides; issue of over-constrained goals during service provisions that arises from flawed or contradicting specification from multiple users should be considered. Apart from that; low training data in general environment setting for individual identification should be addressed. The aim of this research is to establish an integrated system for the human-centric smart home (HcSH) that provides personalized service through loosely coupled devices automatically. This research modularizes the overall system into three modules; which are human identification (HIM); automated planner (APM); and semantic reasoner (SRM). HIM helps select the appropriate QOL; SRM binds the devices by associating them with planning components; which are then used by APM to generate plans for device coordination to maximize QOL fulfillment. Chapter 1 gives the introduction and design motivation. Chapter 2 presents the related works and literature reviews; as well as justifications relevant to this thesis. Chapter 3 deals with HIM; which is realized via face identification. For face identification; problems faced are heavy computational load and insufficient learning data. The solution is to use transfer learning to handle data issue while being able to build generalized face model. For face model refinement; active learning is implemented. Experimental results show the method is competitive in terms of accuracy and computational cost compared to current state of the art. Chapter 4 presents APM; where planning via solving Constraint Satisfaction Problem (CSP) is laid out. CSP in planning is declarative without requiring prior specification of sub-plans; and can handle variables of larger domains. Due to the high possibility of having over-constrained QOL as in practical cases; CSP planner cannot fulfill all of them. An example is a contradicting TV channel request from 2 persons. Optimization through weighted CSP is therefore used to maximize QOL fulfillment. Experiments on weighted CSP shows that the method is capable of performing optimization while generating complex plans. Chapter 5 is on SRM; where knowledge representation is constructed by Web Ontology Language (OWL) description logic. It models knowledge on home and building layout and device functionalities. OWL is used because it is decidable and that it is endorsed by World Wide Web Consortium (W3C). We deal with case studies based on further inference on building state as an important example to discuss the applicability of the proposed method; and demonstrate the use of building ontology. This is followed by automated device binding and the method to generate basic planning components of rules in automated planning. Finally; an extension to robot complex planning is provided to demonstrate how it can be easily extended. Chapter 6 demonstrates the applicability of the HcSH; which integrates all three modules through its implementation in a prototype smart home with 5 rooms; which houses 2 persons. Various tests are performed to show the generated plans are near optimal without redundancy. Œe system is also shown to be scalable given increasing amount of devices. Case studies show that the system can perform well even under short time threshold. Finally; chapter 7 summarizes the thesis. Future vision of the work is also laid out; which is to implement it as a community-centric system.

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tay, N. N. W. (2017). Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化. (Thesis). Tokyo Metropolitan University / 首都大学東京. Retrieved from http://hdl.handle.net/10748/00009960

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tay, Noel Nuo Wi. “Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化.” 2017. Thesis, Tokyo Metropolitan University / 首都大学東京. Accessed January 25, 2021. http://hdl.handle.net/10748/00009960.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tay, Noel Nuo Wi. “Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化.” 2017. Web. 25 Jan 2021.

Vancouver:

Tay NNW. Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化. [Internet] [Thesis]. Tokyo Metropolitan University / 首都大学東京; 2017. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/10748/00009960.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tay NNW. Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化. [Thesis]. Tokyo Metropolitan University / 首都大学東京; 2017. Available from: http://hdl.handle.net/10748/00009960

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


KTH

2. Anzén, Elizabeth. Understanding how automatized personalization with AI can drive value in B2B marketing : A case study of a Swedish industrial equipment manufacturer.

Degree: Industrial Engineering and Management (ITM), 2020, KTH

In the last decade, marketing automation, a tool for automatic personalization, has been gaining significant traction among marketing professionals. In parallel with the growing adoption trend, many marketing automation platform providers have been extending their offers to include AI features. However, there is a lack of research regarding how AI can enhance the process of marketing automation in a way that creates value, which is the studied topic in this thesis. A qualitative and exploratory case study has been conducted in collaboration with the global B2B company Atlas Copco, a manufacturer of industrial equipment. Digital marketing practitioners were presented with two use cases of AI, segmentation and cross-selling, for personalization and asked about the marketing automation process and the expected impact on value. The findings reveal what would be required in the marketing automation process for the use cases in terms of data needs, learning about customer insights, marketing output and evaluation. In our findings value creation strongly revolve around the value types: ‘excellence’, ‘efficiency’ and ‘privacy’. To conclude, AI will enable more advanced personalization and value creation can be substantial if customer sacrifices are addressed in an appropriate way. Depending on relevance, tone of voice, time and use of channel, different feelings of value are perceived, which are factors that AI can help to determine

Under det senaste årtiondet har verktyg för automatisk marknadsföring blivit populära bland marknadsförare. Automatiska marknadsföringsplattformar fungerar som ett verktyg för att automtiskt leverera personaliserade marknadsföring. Många leverantörer av automatiska marknadsföringsplattformar har utökat sina erbjudanden till att innefatta AI-tjänster. Den befintliga forskningen kring hur sådana AItjänster ska utnyttjas på ett sätt som skapar värde är begränsad och därav behandlas ämnet i den här uppsatsen. En explorativ och kvalitativ fallstudie har genomförts i samarbete med Atlas Copco som är ett globalt b2b-företag. Vid varje intervju presenterades antingen merförsäljning eller kundsegmentering sedan ställdes frågor om den automatiska marknadsföringsprocess och värde. Resultaten indikerar vad som skulle krävas för de undersökta användningsfallen i den automatiska marknadsföringsprocessen samt att värdeskapande är starkt kopplat till värdetyperna excellens, effektivitet, privatliv och datasäkerhet. Slutsatserna indikerar att AI kommer göra den personalisering som uppstår till följd av automatisk marknadsföring mer avancerad. Värdeskapandet från nya AI lösningar kan vara signifikant om implementeringen tar hänsyn och adresserar uppoffringar kunder behöver göra.

Subjects/Keywords: AI; B2B; Marketing Automation; Personalization; Value; Value Creation; AI; B2B; automatisk marknadsföring; personalisering; värde; värdeskapande; Engineering and Technology; Teknik och teknologier

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Anzén, E. (2020). Understanding how automatized personalization with AI can drive value in B2B marketing : A case study of a Swedish industrial equipment manufacturer. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279668

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Anzén, Elizabeth. “Understanding how automatized personalization with AI can drive value in B2B marketing : A case study of a Swedish industrial equipment manufacturer.” 2020. Thesis, KTH. Accessed January 25, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279668.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Anzén, Elizabeth. “Understanding how automatized personalization with AI can drive value in B2B marketing : A case study of a Swedish industrial equipment manufacturer.” 2020. Web. 25 Jan 2021.

Vancouver:

Anzén E. Understanding how automatized personalization with AI can drive value in B2B marketing : A case study of a Swedish industrial equipment manufacturer. [Internet] [Thesis]. KTH; 2020. [cited 2021 Jan 25]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279668.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Anzén E. Understanding how automatized personalization with AI can drive value in B2B marketing : A case study of a Swedish industrial equipment manufacturer. [Thesis]. KTH; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279668

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of California – San Diego

3. Verma, Chetan Kumar. Enabling Automated and Efficient Personalization Systems.

Degree: Electrical Engineering (Computer Engineering), 2015, University of California – San Diego

Information explosion and the increasing use of Internet have fueled the growing popularity of personalization systems. Such systems can understand user interests to customize the information served to them, thereby addressing information overload. At the same time, personalization systems can also enable service and content providers to serve targeted advertisements and recommendations to users. In order to operate on the massive scales of the number of users and the amount of data available, personalization systems have a crucial requirement for automation and efficiency. In this dissertation, we identify key challenges faced by personalization systems and provide solutions to address them such that the above requirements can be achieved. We first note that content classification is an important component of personalization systems. Approaches to train classification models typically depend on manual collection and labeling of training data, which makes personalization non-scalable. To address this, we develop a completely automated framework that can provide labeled training data for arbitrary set of categories. Experiments using online videos demonstrate the feasibility and effectiveness of our approach. The second key challenge we address is the sparsity in annotations of popular online content such as Flickr images. Sparse or missing tags hamper the ability of personalization systems to recommend content or to infer the interests of users that access them. Towards this, we show how ontological tag trees can be constructed from corpus based statistics and semantic relationships between tags, to alleviate tag sparsity in a space efficient manner. Through evaluations, we demonstrate the effectiveness and efficiency of ontological tag trees as compared to existing methods. Lastly, we focus on alleviating information overload in enterprise repositories. We design a file metadata based recommendation system that captures per user access patterns and user collaboration to recommend new files. In order to address scalability concerns of per user modeling, we propose optimizations that significantly reduce the time to serve recommendations to users. Experiments over actual enterprise data show that more than two orders of speed up is obtained as a result of the proposed methods.

Subjects/Keywords: Computer science; automation; classification; efficiency; personalization systems; recommendation systems

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Verma, C. K. (2015). Enabling Automated and Efficient Personalization Systems. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/8tq2c9xn

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Verma, Chetan Kumar. “Enabling Automated and Efficient Personalization Systems.” 2015. Thesis, University of California – San Diego. Accessed January 25, 2021. http://www.escholarship.org/uc/item/8tq2c9xn.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Verma, Chetan Kumar. “Enabling Automated and Efficient Personalization Systems.” 2015. Web. 25 Jan 2021.

Vancouver:

Verma CK. Enabling Automated and Efficient Personalization Systems. [Internet] [Thesis]. University of California – San Diego; 2015. [cited 2021 Jan 25]. Available from: http://www.escholarship.org/uc/item/8tq2c9xn.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Verma CK. Enabling Automated and Efficient Personalization Systems. [Thesis]. University of California – San Diego; 2015. Available from: http://www.escholarship.org/uc/item/8tq2c9xn

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.