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Question Answering from Lecture Videos Based on Automatically-Generated 519 We are working on a more intelligent extraction of the concepts and rules from the data sources. All activity applications, e.g. newscasts, theater plays or any kind of speech being complemented by textual data, could be analyzed and annotated with the help of our proposed algorithm. This project was developed in the context of the Web University project 3 which aims to explore novel internet and IT technologies in order to enhance university teaching and research. References 1. Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applica- tions. Cambridge University Press, Cambridge (2003) 2. Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. ACM Press / Addison-Wesley (1999) 3. Bertini, M., Bimbo, A.D., Torniai, C., Cucchiara, R., Grana, C.: Mom: Multimedia ontology manager. a framework for automatic annotation and semantic retrieval of video sequences. In: Bimbo, A.D., Torniai, C., Cucchiara, R., Grana, C. (eds.) ACM SIGMM, pp. 787–788. ACM Press, New York (2006) 4. Engelhardt, M., Hildebrand, A., Lange, D., Schmidt, T.C.: Reasoning about eLearning Multimedia Objects. In: International Workshop on Semantic Web An- notations for Multimedia (SWAMM) (2006) 5. Haubold, A., Kender, J.R.: Augmented segmentation and visualization for presen- tation videos (2005) 6. H¨urst,W.,Kreuzer,T.,Wiesenh¨utter, M.: A qualitative study towards using large vocabulary automatic speech recognition to index recorded presentations for search and access over the web. In: IADIS Internatinal Conference WWW/Internet (ICWI), pp. 135–143 (2002) 7. Jaimes, A., Nagamine, T., Liu, J., Omura, K., Sebe, N.: Affective meeting video analysis. In: IEEE Multimedia and Expo., pp. 1412–1415 (2005) 8. Karam, N., Linckels, S., Meinel, C.: Semantic composition of lecture subparts for a personalized e-learning. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, pp. 716–728. Springer, Heidelberg (2007) 9. Linckels, S., Meinel, C.: Resolving ambiguities in the semantic interpretation of natural language questions. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds.) IDEAL 2006. LNCS, vol. 4224, pp. 612–619. Springer, Heidelberg (2006) 10. Mertens, R., Schneider, H., M¨uller, O., Vornberger, O.: Hypermedia navigation concepts for lecture recordings. In: E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 2480–2847 (2004) 11. Ngo, C W., Wang, F., Pong, T C.: Structuring lecture videos for distance learning applications. In: Multimedia Software Engineering, pp. 215–222 (2003) 12. Porter, M.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980) 13. Repp, S., Linckels, S., Meinel, C.: Towards to an automatic semantic annotation for multimedia learning objects. In: Proceedings of the International Workshop on Educational Multimedia and Multimedia Education 2007, Augsburg, Bavaria, Germany, September 28, 2007, pp. 19–26. ACM, New York (2007) 3 http://www.hpi.uni-potsdam.de/meinel/research/ 520 S. Repp, S. Linckels, and C. Meinel 14. Repp, S., Meinel, C.: Segmenting of recorded lecture videos - the algorithm voic- eseg. In: Proceedings of the 1th Signal Processing and Multimedia Applications (Sigmap), Setubal, Portugal, pp. 317–322 (August 2006) 15. Repp, S., Meinel, C.: Semantic indexing for recorded educational lecture videos. In: 4th IEEE Conference on Pervasive Computing and Communications Workshops (PerCom 2006 Workshops), Pisa, Italy, March 13-17, 2006, pp. 240–245. IEEE Computer Society, Los Alamitos (2006) 16. Repp, S., Waitelonis, J., Sack, H., Meinel, C.: Segmentation and annotation of audiovisual recordings based on automated speech recognition. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds.) IDEAL 2007. LNCS, vol. 4881, pp. 620–629. Springer, Heidelberg (2007) 17. Sack, H., Waitelonis, J.: Integrating social tagging and document annotation for content-based search in multimedia data. In: Semantic Authoring and Annotation Workshop (SAAW) (2006) 18. Schmidt, R.A.: Terminological representation, natural language & relation alge- bra. In: Ohlbach, H.J. (ed.) GWAI 1992. LNCS, vol. 671, pp. 357–371. Springer, Heidelberg (1993) 19. Voorhees, E.M.: The trec-8 question answering track report. In: TREC (1999) 20. W. W. W. C. W3C. OWL Web Ontology Language (2004), http://www.w3.org/ TR/owl-features/ 21. Wolf, P., Putz, W., Stewart, A., Steinmetz, A., Hemmje, M., Neuhold, E.: Lec- turelounge – experience education beyond the borders of the classroom. Interna- tional Journal on Digital Libraries 4(1), 39–41 (2004) 22. Yamamoto, N., Ogata, J., Ariki, Y.: Topic segmentation and retrieval system for lecture videos based on spontaneous speech recognition. In: European Conference on Speech Communication and Technology, pp. 961–964 (2003) F. Li et al. (Eds.): ICWL 2008, LNCS 5145, pp. 521 – 528, 2008. © Springer-Verlag Berlin Heidelberg 2008 An Overview on Mobile E-Learning Research of Domestic and Foreign Yun Yang, Wenan Tan*, Suxian Lin, Xianhua Zhao, and Fujun Yang Software Engineering Institute, Zhejiang Normal University Jinhua, Zhejiang, 321004, P.R. China Tel.: 86-579-82282004; Fax: 86-579-82298188 yangyun662000@yahoo.com.cn, twajsj@sohu.com, linsuxian@126.com, zxhsd@yahoo.cn, yangfujun11@163.com Abstract. Mobile e-Learning is based on the combination of mobile data commu- nication technology and wireless Internet. It is important to study and analyze mo- bile e-Learning research of domestic and foreign, because it will drive the future education and learning markets. This paper summarizes the research on Mobile e-Learning around the whole world and shows clearly construction directions needed toward in China. A systematic discussion and analysis of e-learning pro- viders, educational institutions, and their cooperation is also presented. Keywords: Mobile e-Learning, Wireless Technology, Research Status. 1 Introduction Mobile e-learning (m-Learning) is the exciting art of using mobile technologies to enhance the learning experience (Http://learning.ericsson.net/mlearning2/index.shtml). Mobile phones, PDAs (Personal Digital Assistants), Pocket PCs and the Internet can be blended to engage and motivate learners, any time and anywhere. It is not an online course on a cell phone. For one thing, existing bandwidth and processing power limi- tations make cell phones better suited for handling conversations and real-time data exchange. While third-generation (3G) services [1] make it easier to share applications such as videos and movies on, a mobile phone handset, and the small form factor can make viewing high-fidelity content on a small screen a less-than-satisfying [2] experience. The e-Learning Guild in its recent Mobile Learning report defines mobile learning (or m-Learning as it is also known) as (Http://www.c4lpt.co.uk/handbook/ mobilelearningl.html): “Any activity that allows individuals to be more productive when consuming, interacting with, or creating information, mediated through a compact digital portable device that the individual carries on a regular basis, has reliable con- nectivity, and fits in a pocket or purse.” * Corresponding author. 522 Y. Yang et al. "Portable devices" could be phones, iPhones, smart phones/PDA as well as iPods (and other MP3 players). M-Learning offers a powerful and practical solution to many learning and training challenges (Http://www.ctad.co.uk/content/view/185/277/). For example, it can be used: in collaborative projects and fieldwork; as a classroom alternative to books or computers where learners are widely dispersed; to engage with learners who in the past have felt excluded; in promotional and awareness campaigns, for ‘just-in-time’ em- ployee training [3]. 2 Technology The application of m-Learning is mostly based on the technology of WAP (Wireless Application Protocol), 3G and Bluetooth. The following sections introduce these three kinds of technologies separately. 2.1 WAP WAP is an open international standard for applications that use wireless communica- tion. Its main use is to enable access to the Internet from a mobile phone or PDA. A WAP browser provides all of the basic services of a computer which is based on web browser, but simplified to operate within the restrictions of a mobile phone, such as its smaller view screen. WAP sites are websites written in, or dynamically converted to, WML (Wireless Markup Language) and accessed via the WAP browser. WAP is a protocol for wireless devices like multi media mobile: The bottom-most protocol in the suite is the Wireless Datagram Layer (WDL), which is an adaptation layer that makes every data network look a bit like UDP to the upper layers by providing unreliable transport of data with two 16-bit port numbers (origin and destination). WDL is considered by all the upper layers as one and the same protocol, which has several "technical realizations" on top of other "data bearers" Wireless Transport Layer Security (WTLS) provides a public-key cryptogra- phy-based security mechanism similar to TLS (Transport Layer Security). Its use is optional. Wireless Transaction Layer (WTL) provides transaction support (reliable re- quest/response) that is adapted to the wireless world. WTL supports more ef- fectively than TCP on the problem of packet loss, which is common in 2G wireless technologies in most radio conditions. Wireless Session Layer (WSL) is best thought of on first approach as a com- pressed version of HTTP. This protocol suite allows a terminal to emit requests that have an HTTP or HTTPS equivalent to a WAP gateway; the gateway translates requests into plain HTTP. Finally, Wireless Application Environment (WAE), in this space, applica- tion-specific markup language is defined. The primary language of the WAE is WML, which has been designed from scratch for handheld devices with phone-specific features [4]. An Overview on Mobile E-Learning Research of Domestic and Foreign 523 2.2 3G 3G is the third generation of mobile phone standards and technology, superseding 2G. The International Telecommunication Union (ITU) defined the demands for 3G mobile networks with the IMT-2000 (International Mobile Telecommunication) standard. An organization called 3rd Generation Partnership Project (3GPP) has con- tinued that work by defining a mobile system that fulfills the IMT-2000 standard. This system is called Universal Mobile Telecommunications System (UMTS). Until Octo- ber 19, 2007, there are three mainstream wireless interface standard on 3G technology: W-CDMA (Wideband Code Division Multiple Access), CDMA2000, TD-SCDMA (Time Division -Synchronous CDMA), they are proposed and applied mostly in Europe, Korea (Japan and America), and China respectively. 3G technologies enable network operators to offer users a wider range of more ad- vanced services while achieving greater network capacity through improved spectral efficiency. Services include wide-area wireless voice telephony, video calls, and broadband wireless data, all in a mobile environment. Additional features also include HSPA (high speed packet access) data transmission capabilities, and are able to deliver 14.4Mbit/s on the downlink and 5.8Mbit/s on the uplink. Unlike IEEE 802.11 networks, 3G networks are wide area cellular telephone net- works which evolved to incorporate high-speed internet access and video telephony. IEEE 802.11 (common names Wi-Fi or WLAN) networks are short range, high-bandwidth networks primarily developed for data [5]. 2.3 Bluetooth Bluetooth is a wireless protocol utilizing short-range communications technology, facili- tating both voice and data transmissions over short distances from fixed and/or mobile devices, creating wireless personal area networks (PANs). It provides a way to connect and exchange information between devices such as mobile phones, Telephones, laptops, personal computers, printers, GPS receivers, digital cameras, and video game consoles over a secure, globally unlicensed Industrial, Scientific, and Medical (ISM) in 2.4 GHz short-range radio frequency bandwidth. Bluetooth is a standard and communications protocol primarily designed for low power consumption, with a short range (power-class-dependent: 1 meter, 10 meters, 100 meters) based on low-cost transceiver microchips in each device. Bluetooth en- ables these devices to communicate with each other when they are in range. The de- vices use a radio communications system, so they do not have to be in line of sight of each other, and can even be in other rooms, as long as the received transmission is powerful enough. Bluetooth device class indicates the type of device and the supported services of which the information is transmitted during the discovery process [4]. Sections below are applications of overseas research on m-Learning as well as Mobile e-learning in China. 3 Overseas Research of M-Learning Overseas research of m-Learning has emerged in recent four years. At the beginning of 21st century, with the increasing number of companies specialized in e-Learning, . (2007) 3 http://www.hpi.uni-potsdam.de/meinel/research/ 520 S. Repp, S. Linckels, and C. Meinel 14. Repp, S., Meinel, C.: Segmenting of recorded lecture videos - the algorithm voic- eseg. In: Proceedings of the 1th Signal Processing. e-learning. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, pp. 716–728. Springer, Heidelberg (2007) 9. Linckels, S., Meinel, C.: Resolving ambiguities in the semantic interpretation. make viewing high-fidelity content on a small screen a less-than-satisfying [2] experience. The e-Learning Guild in its recent Mobile Learning report defines mobile learning (or m-Learning as

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