The recognized importance of coffee alkaloids and phenolics mediating insect-plant interactions led to the present investigation aiming to test the hypothesis that the phenolics chlorogenic and caffeic acids and the alkaloid caffeine and some of its derivatives present in coffee leaves affect egg-laying by the coffee leaf miner Leucoptera (=Perileucoptera) coffeella (Guérin-Méneville & Perrotte...

Discovering functional dependencies (FDs) from an existing relation instance is an important technique in data mining and database design. To date, even the most e cient solutions are exponential in the number of attributes of the relation (n), even when the size of the output is not exponential in n. Lopes et al. developed an algorithm, Dep-Miner, that works well for large n on randomly-genera...

Many Web sites, including blogs, online stores, and some database Web sites, give users the ability to state their opinions about the products they buy and use. This is a serious concern for many companies because of the potential damage of reputation. Companies want to monitor and gauge customers’ opinions, but they do not have the time or resources to manually gather statistics on this ever-e...

A deep-ocean test miner has not only coupled relationship between component systems, but also various design requirements of each system to accomplish the specified multi-tasks. To meet the multiobjectives of the complex system, multidisciplinary design optimization (MDO) is performed. Metamodels such as kriging model and response surface model are employed to reduce computational costs for MDO...

Identifying and analyzing aspectual requirements manually is very resource intensive due to the broadly scoped nature of aspects and the large volumes and ambiguity of requirements elicitation data. In this paper we present an evaluation of EA-Miner – a requirements-level aspect identification tool. The tool is evaluated by comparing the performance of an analyst using the tool with that of car...

Classification and clustering are powerful and popular data mining techniques. Organizations use them to capture information, retain customers, and improve business performance. This paper presents a method for selecting data mining software for an academic environment based on its classification and clustering tools. This research applies the data mining software evaluation framework to evalua...

Common sense collection has long been an important subfield of AI. This paper introduces a combined architecture for commonsense harvesting by text mining and a game with a purpose. The text miner module uses a seed set of known facts (sampled from ConceptNet) as training data and produces candidate commonsense facts mined from corpora. The game module taps humans’ knowledge about the world by ...

In this paper, a fuzzy frequent itemset (FFI)-Miner algorithm is developed to mine the complete set of FFIs without candidate generation. It uses a novel fuzzy-list structure to keep the essential information for later mining process. An efficient pruning strategy is also developed to reduce the search space, thus speeding up the mining process to directly discover the FFIs. Experiments are con...

Chemical probes are essential tools for understanding biological systems and for target validation, yet selecting probes for biomedical research is rarely based on objective assessment of all potential compounds. Here, we describe the Probe Miner: Chemical Probes Objective Assessment resource, capitalizing on the plethora of public medicinal chemistry data to empower quantitative, objective, da...

The effective application of a data mining process is littered with many difficult and technical decisions (i.e. data cleansing, feature transformations, algorithms, parameters, evaluation). Subsequently, most data mining products provide a large number of models and tools, but few provide intelligent assistance for addressing the above-mentioned challenges that face the non-specialist data min...