We formally define multi-resource bin packing, a generalization of conventional bin packing, and develop an algorithm called Reordering Grouping Genetic Algorithm (RGGA) to solve this problem. Multi-resource bin packing can be applied to different problems, such as placing virtual machines onto servers. We first test RGGA on conventional bin packing problems and show that it yields excellent re...

This paper presents an unsupervised relation extraction algorithm, which induces relations between entity pairs by grouping them into a “natural” number of clusters based on the similarity of their contexts. Stability-based criterion is used to automatically estimate the number of clusters. For removing noisy feature words in clustering procedure, feature selection is conducted by optimizing a ...

This paper proposes a framework of supervised model learning that realizes feature grouping to obtain lower complexity models. The main idea of our method is to integrate a discrete constraint into model learning with the help of the dual decomposition technique. Experiments on two well-studied NLP tasks, dependency parsing and NER, demonstrate that our method can provide state-of-the-art perfo...

this study set out to investigate the distribution of the syntactic properties associatedwith the prodrop parameter by persian-speaking l2 learners of english in an attemptto examine the (un)attainability of native-like knowledge and (in)accessibility of ugin adult sla. to do so, 92 participants were assigned into different levels of l2knowledge based on their performances on the oxford placeme...

This paper presents an unsupervised word sense learning algorithm, which induces senses of target word by grouping its occurrences into a “natural” number of clusters based on the similarity of their contexts. For removing noisy words in feature set, feature selection is conducted by optimizing a cluster validation criterion subject to some constraint in an unsupervised manner. Gaussian mixture...

A lex.[ca].[sod g t '&mlnaF formalism has been developed that a].lovas constraints to be specified between 'demand' ~and 'source' ~;or'ds (e.g., between verb and its karaka roles). The parser has two important novel features: (.[) It has a local word grouping phase in uhich wot"d gr'oups are formed using 'local' infor-marion onl~ ~. They are formed based on finite state machine specifications t...

As a collection of entities with common goals, supply chain (SC) has a unique system structure. Taxonomy is the mechanism for collecting, structuring, and classifying information about a system. This paper proposes taxonomy for SC system. It is built around a dynamic constraint network that describes SC relationships in time among its product, process, and resource components. SC characteristic...

Referential integrity is an essential global constraint in a relational database, that maintains it in a complete and consistent state. In this work, we assume the database may violate referential integrity and relations may be denormalized. We propose a set of quality metrics, defined at four granularity levels: database, relation, attribute and value, that measure referential completeness and...

Color processing imposes a new constraint on stereo vision algorithms: The assumption of constant color on object surfaces used to align local correlation windows with object boundaries has improved the accuracy of recent window based stereo algorithms significantly. While several algorithms have been presented that work with adaptive correlation windows defined by color similarity, only a few ...