A Domain-Independent Text Segmentation Method for Educational Course Content

Author(s):  
Yuwei Tu ◽  
Ying Xiong ◽  
Weiyu Chen ◽  
Christopher Brinton
2020 ◽  
Vol 21 (2) ◽  
pp. 153-163
Author(s):  
Nor Farahidah Za'bah ◽  
Ahmad Amierul Ashraf Muhammad Nazmi ◽  
Amelia Wong Azman

Segmentation is an important aspect of translating finger spelling of sign language into Latin alphabets. Although the sign language devices that are currently available can translate the finger spelling into alphabets, there is a limitation where the output is stored in a long continuous string without spaces between words. The system proposed in this work is meant to be used together with a text-generating glove device. The system used text input string and the string is then fed into the system, one character at a time, and then it is segmented into words that is semantically correct. The proposed text segmentation method in this work is by using the dynamic programming and back-off algorithm, together with the probability score using word matching with an English language text corpus. Based on the results, the system is able to properly segment words with acceptable accuracy. ABSTRAK: Segmentasi adalah aspek penting dalam menterjemahkan ejaan bahasa isyarat ke dalam huruf Latin. Walaupun terdapat peranti bahasa isyarat yang menterjemahkan ejaan jari menjadi huruf, namun begitu, huruf-huruf yang dihasilkan disimpan dalam rentetan berterusan yang panjang tanpa jarak antara setiap perkataan. Sistem yang dicadangkan di dalam jurnal ini akan diselaraskan bersama dengan sarung tangan bahasa isyarat yang boleh menghasilkan teks. Sistem ini akan mengambil rentetan input teks di mana huruf akan dimasukkan satu persatu dan huruf-huruf itu akan disegmentasikan menjadi perkataan yang betul secara semantik. Kaedah pembahagian yang dicadangkan ialah segmentasi yang menggunakan pengaturcaraan dinamik dan kaedah kebarangkalian untuk mengsegmentasikan huruf-huruf tersebut berdasarkan padanan perkataan dengan pengkalan data di dalam Bahasa Inggeris. Berdasarkan hasil yang telah diperolehi, sistem ini berjaya mengsegmentasikan huruf-huruf tersebut dengan berkesan dan tepat.


Author(s):  
Samuel Wood ◽  
David Richardson ◽  
Simon Roberts

Consideration of a learners’ biography is deemed to impact on their engagement with formal education and their connection with, and perceived relevance of, educational course content. It is considered equally important to understand coaches who enrol on formal coach learning in sport—their motivations, beliefs, values, existing knowledge, and previous life experiences. This research explored the individual biographies of eight neophyte cycling coaches over an 18-month period following the successful completion of a national governing body coach award. Following 23 formal semistructured interviews and 26 unstructured interviews, deductive thematic narrative analysis revealed three different typologies of coach: the “performance coach”; the “parent-coach”; and the “community coach.” Although the subjective details of the life stories varied according to their idiosyncratic perspective, all participants’ stories broadly followed one of these three identifiable narratives. Identifying different “typologies” of cycling coaches’ answers calls from coach developers to account for the specific backgrounds of coaches’ practices. It is hoped this research will begin the process of developing more personalised approaches to coach education.


2019 ◽  
Vol 18 (02) ◽  
pp. 649-671 ◽  
Author(s):  
Ning Wang ◽  
Shanhui Ke ◽  
Yibo Chen ◽  
Tao Yan ◽  
Andrew Lim

In this paper, text mining and statistical models are deployed to explore the relationship between the Shanghai Stock Exchange Composite Index (SSECI) and the collective emotions of individual investors. The emotions of individual investors are quantified by extracting and aggregating investor online posts that contain finance-related keywords. To identify a set of finance-related keywords, three years of blogs from a famous financial blog site are segmented by an automatic text segmentation method; meanwhile, in the literature of social media, people typically select keywords manually. Posts that discuss the keywords are extracted out of all types of topics from Sina Weibo, the largest microblog platform in China. Statistical results reveal the relationship between daily posts and daily opening prices with a one-day lag, which indicates the existence of information (news) propagation lag. This study contributes to the existing literature by demonstrating that the microblog sentiment level reports can be quantitatively incorporated as a proxy to provide valuable support to portfolio decision making.


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