We introduce a new dataset of logical entailments for the purpose of measuring models' ability to capture and exploit the structure of logical expressions against an entailment prediction task. We use this task to compare a series of architectures which are ubiquitous in the sequence-processing literature, in addition to a new model class-PossibleWorldNets-which computes entailment as a "convolution over possible worlds". Results show that convolutional networks present the wrong inductive bias for this class of problems relative to LSTM RNNs, treestructured neural networks outperform LSTM RNNs due to their enhanced ability to exploit the syntax of logic, and PossibleWorldNets outperform all benchmarks.
In turbulent, highly competitive markets corporate organisations are faced with the dichotomy of`d ownsizing'' their costs, yet at the same time improving the service that they offer their customers. This paper shows how a more market-orientated approach can bring greater benefits for companies. Additional``soft'' services can help to tailor a package of customer service and provide product and service differentiation, while inverting the traditional organisational structure can bring customer and supplier closer and lead to greater collaboration. This requires more open communication systems for the rapid capture, transfer and management of information. This has proved difficult in the past, but Web-based technology is changing all of that. The paper concludes that all of these features are essential for a customer-supplier interaction model that can provide the customer with added value in product and service delivery, and the supplier with increased business opportunities.
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