in this context and for helping to manufacturing industries in this research an attempt has been made to provide a method to managers of evaluating and ranking of agility strategies by using of a fuzzy inference system which is a branch of artificial intelligence. this research has been performed in three sequential phases. firstly, some variables, as factors of agility drivers, agility capabil...

background; the performance of the hse units has various dimensions leading to different performances. thus, any industry should be capable of evaluating these systems. the aim of this study was to design a standard questionnaire in the field of performance evaluation of hse management system employing balanced score card model. methods; in this study we, first determined the criteria to be eva...

In this paper we present the TakeLab-QA entry to SemEval 2017 task 3, which is a question-comment re-ranking problem. We present a classification based approach, including two supervised learning models – Support Vector Machines (SVM) and Convolutional Neural Networks (CNN). We use features based on different semantic similarity models (e.g., Latent Dirichlet Allocation), as well as features ba...

This paper describes the system deployed by the CLaC-EDLK team to the SemEval 2016, Complex Word Identification task. The goal of the task is to identify if a given word in a given context is simple or complex. Our system relies on linguistic features and cognitive complexity. We used several supervised models, however the Random Forest model outperformed the others. Overall our best configurat...

LPMP West Sumatra is a company in the technical implementation department of Ministry Education and led by leadership responsible to Director General for Improving Quality Educators Personnel (PMPTK). The selection process hiring contract employees has difficulties because system still manual where all processes from initial stage registration final are done manually so it takes quite long time...

In this paper, we deal with efficiency of the diversification of results returned by Web Search Engines (WSEs). We extend a search architecture based on additive Machine Learned Ranking (MLR) systems with a new module computing the diversity score of each retrieved document. Our proposed solution is designed to be used with other techniques, (e.g. early termination of rank computation, etc.). F...

In this paper we are reporting the results obtained participating in the “Evaluating Word Sense Induction and Discrimination Systems” task of Semeval 2007. Our totally unsupervised system performed an automatic self-term expansion process by mean of co-ocurrence terms and, thereafter, it executed the unsupervised KStar clustering method. Two ranking tables with different evaluation measures wer...

We present ERSS 2005, our entry to this year’s DUC competition. With only slight modifications from last year’s version to accommodate the more complex context information present in DUC 2005, we achieved a similar performance to last year’s entry, ranking roughly in the upper third when examining the ROUGE-1 and Basic Element score. We also participated in the additional manual evaluation base...

We participated in the matching and ranking subtask in TRECVid challenge 2017. The task here was to return a ranked list of the most likely text descriptions that correspond to each video. We adopted a joint visual semantic embedding approach for image-text retrieval and applied to the video-text retrieval task utilizing key-frames extracted by dissimilaritybased sparse subset selection approac...

The paper proposes formulating MT evaluation as a ranking problem, as is often done in the practice of assessment by human. Under the ranking scenario, the study also investigates the relative utility of several features. The results show greater correlation with human assessment at the sentence level, even when using an n-gram match score as a baseline feature. The feature contributing the mos...