The archiving and maintenance of vast quantities of data is a key challenge for the current use of information technology. When storing large repositories, possibly mirrored at multiple sites, an archiving system aims to reduce both storage and transmission costs. Delta compression is a key component of many archiving and backup systems. A file may be stored succinctly as a sequence of referenc...

Here we respond to some comments by Alday concerning headedness in linguistic theory and the validity of the assumptions of a mathematical model for word order. For brevity, we focus only on two assumptions: the unit of measurement of dependency length and the monotonicity of the cost of a dependency as a function of its length. We also revise the implicit psychological bias in Alday’s comments...

We present a language model consisting of a collection of costed bidirectional finite state automata associated with the head words of phrases. The model is suitable for incremental application of lexical associations in a dynamic programming search for optimal dependency tree derivations. We also present a model and algorithm for machine translation involving optimal “tiling” of a dependency t...

Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data dependency, consume more resources, and do not support streaming data. This paper proposes online LML model (OAMC) to support streaming data with reduced ...

We present a cost-effective strategy for the creation of a mid-size fine-grained Spanish dependency tree bank of surface-, deep-syntactic and semantic structures as defined in the Meaning-Text Theory. The strategy starts from a small seed dependency corpus, the AnCora corpus, whose annotation is considerably more coarse-grained than our target annotation. We show that this discrepancy can be br...

We present a cost effective strategy for the creation of a mid-size fine-grained dependency treebank of surfaceand deep-syntactic structures as defined in the Meaning-Text Theory for Spanish. The strategy starts from a small seed dependency corpus, the AnCora corpus, whose annotation is considerably more coarse-grained than our target annotation. We show that this discrepancy can be bridged lar...

Natural language processing (NLP) annotation projects employ guidelines to maximize inter-annotator agreement (IAA), and models are estimated assuming that there is one single ground truth. However, not all disagreement is noise, and in fact some of it may contain valuable linguistic information. We integrate such information in the training of a cost-sensitive dependency parser. We introduce f...

Stochastic dependency parsers can achieve very good results when they are trained on large corpora that have been manually annotated. Active learning is a procedure that aims at reducing this annotation cost by selecting as few sentences as possible that will produce the best possible parser. We propose a new selective sampling function for Active Learning that exploits two memory-based distanc...

It is well known that causal consistency is more expensive to implement than eventual consistency due to its requirement of dependency tracking and checking for causality. To close the performance gap between the two consistency models, we propose a new protocol that implements causal consistency for both partitioned and replicated data stores. Our protocol trades the visibility latency of upda...

Behjati S, Jamieson K, Montgomery M, et al. Arch Dis Child (2010). doi:10.1136/adc.2010.206201 1 of 1 REFERENCES 1. NHS Executive . Paediatric Intensive Care: A Framework for the Future. London : HMSO , 1997 . 2. Crawford N, Powell CVE. High dependency care. Curr Paediatr 2004 ; 14 : 197 – 201 . 3. Datt C, Robinson K. Improving paediatric high dependency provision at a district general hospital...