XML documents clustering using a tensor space model

The traditional Vector Space Model (VSM) is not able to represent both the structure and the content of XML documents. This paper introduces a novel method of representing XML documents in a Tensor Space Model (TSM) and then utilizing it for clustering. Empirical analysis shows that the proposed method is scalable for large-sized datasets; as well, the factorized matrices produced from the proposed method help to improve the quality of clusters through the enriched document representation of both structure and content information

XML Schema Clustering with Semantic and Hierarchical Similarity Measures

With the growing popularity of XML as the data representation language, collections of the XML data are exploded in numbers. The methods are required to manage and discover the useful information from them for the improved document handling. We present a schema clustering process by organising the heterogeneous XML schemas into various groups. The methodology considers not only the linguistic and the context of the elements but also the hierarchical structural similarity. We support our findings with experiments and analysis

Improving Recommendation Novelty Based on Topic Taxonomy

Clustering has been a widely applied approach to improve the computation efficiency of collaborative filtering based recommendation systems. Many techniques have been suggested to discover the item-to-item, user-to- user, and item-to-user associations within user clusters. However, there are few systems utilize the cluster based topic-to-topic associations to make recommendations. This paper suggests a taxonomy-based recommender system that utilizes cluster based topic-to-topic associations to improve its recommendation quality and novelty

Data Mining for Web-Enabled Electronic Business Applications

Web-enabled electronic business is generating massive amounts of data on customer purchases, browsing patterns, usage times, and preferences at an increasing rate. Data mining techniques can be applied to all the data being collected for obtaining useful information. This chapter attempts to present issues associated with data mining for Web-enabled electronicbusiness. Copyright Idea Group Inc

PRARANCANGAN PABRIK BIOETANOL DARI POD KAKAO (THEOBROMA COCOA L) DENGAN KAPASITAS PRODUKSI 15.000/TAHUN

ABSTRAKPrarancangan Pabrik Bioetanol ini menggunakan Pod Kakao sebagai bahan baku. Kapasitas produksi Pabrik Bioetanol ini adalah 15.000 ton/tahun dengan hari kerja 330 hari/tahun. Bentuk perusahaan yang direncanakan adalah Perseroan Terbatas (PT) dengan menggunakan metode struktur garis dan staf. Kebutuhan tenaga kerja untuk menjalankan perusahaan ini berjumlah 160 orang. Lokasi pabrik direncanakan didirikan di kecamatan Tanah Luas, Kabupaten Aceh Utara, Provinsi Nanggroe Aceh Darussalam dengan luas tanah 26.400 m2. Sumber air Pabrik Bioetanol ini berasal dari Sungai Kr. Pasee, Kabupaten Aceh Utara, Provinsi Nanggroe Aceh Darussalam dan untuk memenuhi kebutuhan listrik diperoleh dari Perusahaan Listrik Negara (PLN) dan Generator dengan daya 2.934 kW.Hasil analisa ekonomi yang diperoleh adalah :a.Fixed Capital Investment= Rp.152.783.793.868b.Working Capital Investment= Rp.30.342.575.885c.Total Capital Investment= Rp.183.126.369.753d.Total Biaya Produksi= Rp.225.320.891.428e.Hasil Penjualan= Rp.313.852.500.000f.Laba Bersih= Rp.66.398.706.428g.Rate of Return (IRR)= 16,07%h.Pay Out Time (POT) = 6 tahun 8 bulani.Break even Point (BEP) = 52