A Cultural Heritage Forum Celebrating Technological Innovation at Station X

We aim to encourage and support public participation in heritage through the development of Cultural Heritage Forums, a kind of cultural web portal that enables active participation of communities of interest in a way that complements rather than replaces visits to physical cultural institutions. The cultural heritage forum described here (Station X) is concerned with promoting an understanding of technology innovation in the areas of computing and cryptography. We propose a number of scenarios concerning how the forum can be designed, drawing on our earlier work in using knowledge modelling and text analysis to support the exploration of digital resources

A Modified Overlapping Partitioning Clustering Algorithm for Categorical Data Clustering

Clustering is one of the important approaches for Clustering enables the grouping of unlabeled data by partitioning data into clusters with similar patterns. Over the past decades, many clustering algorithms have been developed for various clustering problems. An overlapping partitioning clustering (OPC) algorithm can only handle numerical data. Hence, novel clustering algorithms have been studied extensively to overcome this issue. By increasing the number of objects belonging to one cluster and distance between cluster centers, the study aimed to cluster the textual data type without losing the main functions. The proposed study herein included over twenty newsgroup dataset, which consisted of approximately 20000 textual documents. By introducing some modifications to the traditional algorithm, an acceptable level of homogeneity and completeness of clusters were generated. Modifications were performed on the pre-processing phase and data representation, along with the number methods which influence the primary function of the algorithm. Subsequently, the results were evaluated and compared with the k-means algorithm of the training and test datasets. The results indicated that the modified algorithm could successfully handle the categorical data and produce satisfactory clusters

Implemetasi Fuzzy Logic Based Ranking Function Dalam Sistem Informasi Pencarian Artikel Pariwisata Berbasis Mobile

Kebutuhan manusia terhadap perkembangan teknologi informasi semakin meningkat. Begitu pula dengan kebutuhan manusia untuk mendapatkan sebuah informasi dengan cepat. Sebuah informasi didapatkan dengan menggunakan sebuah sistem temu kembali informasi yang mengembalikan sejumlah dokumen relevan dari sebuah dataset yang besar sesuai dengan query masukan pengguna. Pengembalian informasi relevan ini dilakukan berdasarkan hasil pembobotan dokumen dengan menggunakan metode tertentu. Metode paling umum yang digunakan dalam pembobotan dokumen adalah pembobotan TF – IDF( term frequency-inverse document frequency) yang merupakan hasil perkalian term frequency dengan inverse document frequency. Pada Tugas Akhir ini akan diimplementasikan sebuah metode pembobotan dokumen yang menggunakan pendekatan fuzzy untuk meningkatkan akurasi dari sebuah sistem temu kembali informasi. Metode tersebut akan menggunakan beberapa elemen yang sering digunakan dalam pembobotan dokumen, seperti term frequency, inverse document frequency dan normalization. Metode ini akan melakukan pendekatan fuzzy dengan 2 level untuk menghitung nilai relevansi dari sebuah dokumen. Hasil uji coba menunjukkan metode dengan pendekatan fuzzy menghasilkan nilai precision dan recall yang lebih baik jika dibandingkan dengan metode non fuzzy. ========== Human needs to the development of information technology is increasing. Similarly, the human need to obtain an information quickly. Information obtained using an information retrieval system that returns a number of relevant documents from a large dataset in accordance with the user input query. Relevant information retrieval is done based on the weighting of the document by using certain methods. The most common method used in weighting the document is TF – IDF(term frequencyinverse document frequency) weighting which is the result of the multiplication term frequency by inverse document frequency. In this final project will be implemented a document weighting method that uses fuzzy approach to improve the accuracy of an information retrieval system. The method uses several elements that are often used in weighting the document, such as term frequency, inverse document frequency and normalization. This method will perform two level fuzzy approach to calculate the relevance of a document Experiment results show the method with fuzzy approach generate better precision and recall value when compared to nonfuzzy method

Analyzing Trends and Topics in Internet Governance and Cybersecurity Debates Found in Twelve Years of IGF Transcripts

Internet Governance research generates substantial and innovative, interdisciplinary global scholarship. What are key topics and themes in this research area, and how do they relate to cybersecurity? This paper answers these questions by analyzing transcripts from twelve years of the UN Internet Governance Forum (IGF), asking: (1) What key themes, topics, and entities are discussed at IGF? (2) Which issues have remained consistent at IGF, and which have changed? And (3) to what extent is the NIST Cybersecurity Framework represented at IGF? Using the CRISP-DM approach to text mining, we find human rights as the most dominant IGF theme, followed by freedom of expression, with disability being a persistent issue. During entity extraction cybersecurity emerges prominently, as does blockchain and IoT. Topic Modeling illustrates the resilience of human rights, but also identifies the IANA transition, accessibility, and “fake news.” Finally, the NIST cybersecurity framework is represented clearly in the data

Impact of Event Recommendation Systems in User\u27s Decision Making

Thesis (Master of Science in Informatics)--University of Tsukuba, no. 37777, 2017.3.2