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The use of mobile devices such as smartphones, tablets, smart watches and notebooks in the agriculture sector is gaining significant popularity. Through mobile technologies, farmers are aided to quickly and easily communicate, advertise goods and services, as well as accessing agronomic data in soft-real time. Though mobile devices are a good source of agronomic information access and dissemination,...
The modern data economy, which has been described as "Big Data", has changed the status quo on digital content creation and storage. While data storage has followed the schema-dictated approach for decades, the recent nature of digital content, which is widely unstructured, creates the need to adopt different storage techniques. Thus, the NoSQL database systems have been proposed to accommodate...
The diversity of the mobile landscape is shaping the business outlook of several enterprises including the agricultural sector. Today, there are several opportunities that can be harnessed in terms of productivity, mechanization, revenue, and so on when mobile technology is combined with agriculture technology. Especially, with mobile apps, agriculturists such as crop farmers can have access to timely...
Unstructured data mining has become topical recently due to the availability of high-dimensional and voluminous digital content (known as "Big Data") across the enterprise spectrum. The Relational Database Management Systems (RDBMS) have been employed over the past decades for content storage and management, but, the ever-growing heterogeneity in today's data calls for a new storage approach...
One of the major challenges of the "Big Data" epoch is unstructured data mining. The problem arises due to the storage of high-dimensional data that has no standard schema. While knowledge discovery in database (KDD) algorithms were designed for data extraction, the algorithms best fit for structured data storages. Moreover, today, at the data storage level, NoSQL databases have been deployed...
While “Big data” has brought good tidings in terms of easy accessibility to voluminous data, we are faced with challenges too. The existing Knowledge Discovery in Database (KDD) processes which have been proposed for schema-oriented data sources are no longer applicable since todays data is unstructured. Previously, we deployed a tool called TouchR which relies on the Hidden Markov Model (HMM) to...
The major challenge that the big data era brings to the services computing landscape is debris of unstructured data. The high-dimensional data is in heterogeneous formats, schemaless, and requires multiple storage APIs is some cases. This situation has made it almost impractical to apply existing data mining techniques which are designed for schema-based data sources in a knowledge discovery in database...
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