Now showing items 1-6 of 6

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    Alternating Least Squares with Incremental Learning Bias 

    Aung, Than Htike; Rachsuda Jiamthapthaksin (2015)

    Recommender systems provide personalized suggestions for every individual user in the system. Many recommender systems use collaborative filtering approach in which the system collects and analyzes users' past behaviors, activities or preferences to produce high quality recommendations for the users. Among various collaborative recommendation techniques, model-based approaches are more scalable than memory-based approaches for large scale data sets in spite of large offline computation and difficulty to update the model in real time. In this ...
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    Clustering Analysis on Alumni Data Using Abandoned and Reborn Particle Swarm Optimization 

    Paulus Mudjihartono; Thitipong Tanprasert; Rachsuda Jiamthapthaksin (2016-02)

    Alumni data is one of the most important data that university management uses for developing the learning process decisions. This paper applies the idea of Abandoned and Reborn PSO (AR-PSO) to convert a clustering problem into the optimization form with an objective function to minimize the ugliness of the desired clusters. This algorithm of Clustering using AR-PSO (CAR-PSO) is slightly adapted to the cluster problem domain. The generated clusters need to be examined to decide if they are acceptable. There are three evaluations; the closeness, ...
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    Dimension Independent Cosine Similarity for Collaborative Filtering using MapReduce 

    Shen, Fei; Rachsuda Jiamthapthaksin (2016-02)

    DIMSUM, an efficient and accurate all-pair similarity algorithm for real-world large scale dataset, tackles shuffle size problem of several similarity measures using MapReduce. The algorithm uses a sampling technique to reduce `power items' and preserves similarities. This paper presents an improved algorithm DIMSUM+ with a complex sampling technique to enhance DIMSUM so that it is able to further reduce `power users'. The algorithm generates k-nearest-neighbor matrix that are used in collaborative based Recommender systems. The evaluations of ...
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    A Framework of Incorporating Thai Social Networking Data in Online Marketing Survey 

    Nitipan Ratanasawadwat; Rachsuda Jiamthapthaksin; Than Htike Aung (2016)

    With the introduction of high-speed Internet and smartphones at an affordable price range, many Thai citizens possess smartphones and utilize them as part of their daily life activities. The high mobile phones penetration and social networking usage is conductive to new approaches in performing marketing survey. This research proposes a framework that automatically incorporates Thai social networking data with online marketing survey for marketing analysis. In particular, it provides online marketing survey to a respondent, and automatically ...
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    Fuzzy information retrieval with respect to graded features 

    Rachsuda Jiamthapthaksin (Bangkok : Assumption University, 1999)
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    A System for Popular Thai Slang Extraction from Social Media Content with N-Gram Based Tokenization (KST 2016) 

    Rachsuda Jiamthapthaksin; Pisal Setthawong; Nitipan Ratanasawetwad (2016-02)

    With increased penetration of smart devices and internet connectivity, many Thais are more readily engaged in social media, online forums, and chat groups. As there is an increased consumption of social media content, there is a shift from the consumption of traditional medias in which formal language are used regularly such as broadcast and traditional print medias. Social media posts are a reflection of the trend, where posts usually made by younger generations usually involve communication in slang and non-formal language which is not typically ...