With the evolution of internet, author profiling has become a topic of great interest in the field of forensics, security, marketing, plagiarism detection etc. However the task of identifying the characteristics of the author just based on a text document has its own limitations and challenges. This paper reports on the design, techniques and learning models we adopted for the PAN-2014 Author P...

This paper explores how to extend the dependency pair technique for proving termination of higher-order rewrite systems. In the first order case, the termination of term rewriting systems are proved by showing the non-existence of an infinite R-chain of the dependency pairs. However, the termination and the non-existence of an infinite R-chain do not coincide in the higher-order case. We introd...

This paper describes the system used by the LIPN-IIMAS team in the Task 2, Semantic Textual Similarity, at SemEval 2015, in both the English and Spanish sub-tasks. We included some features based on alignment measures and we tested different learning models, in particular Random Forests, which proved the best among those used in our participation.

We collect together here the concepts and results which we will need in the sequel; details and proofs are to be found in [HP 1, 2]. Let X1, X2, · · · , Xk be independently distributed random integer variables such that Xj takes values in the range 1 ≤ Xj ≤ nj with equal likelihood. Let m be a fixed but arbitrary modulus. We refer to (n1, n2, · · · , nk;m), abbreviated to (n, k;m), as a system....

In this studywe compared the performance of regression tree ensembles using hyperspectral data. More specifically, we compared the performance of bagging, boosting and random forest to predict Sirex noctilio induced water stress in Pinus patula trees using nine spectral parameters derived from hyperspectral data. Results from the study show that the random forest ensemble achieved the best over...

In this work an experimental study about the capability of the LBP, HOG descriptors and color for clothing attribute classification is presented. Two different variants of the LBP descriptor are considered, the original LBP and the uniform LBP. Two classifiers, Linear SVM and Random Forest, have been included in the comparison because they have been frequently used in clothing attributes classi...

This paper proposes the use of data available at Manchester Metropolitan University to assess the variables that can best predict student progression. We combine Virtual Learning Environment and MIS student records data sets and apply the Random Forest (RF) algorithm to ascertain which variables can best predict students’ progression (students satisfactorily completing one year and passing to t...

We examine the interplay between two important decisions that impact environmental performance in a production setting: inspections performed by a regulator and noncompliance disclosure by a production …rm. To preempt the penalty that will be levied once a compliance violation is discovered in an inspection, the …rm dynamically decides whether it should disclose a random occurrence of noncompli...

One of the most common approaches for handling the multiclass classification problem is to divise the original data set into binary subclasses and to use a set of binary classifiers in order to solve the binarization problem. A new method for solving multi-class classification problems is proposed, by incorporating random resampling techniques in the one-versus-all strategy. Specifically, the d...

We describe the SEERLAB system that participated in the SemEval 2010’s Keyphrase Extraction Task. SEERLAB utilizes the DBLP corpus for generating a set of candidate keyphrases from a document. Random Forest, a supervised ensemble classifier, is then used to select the top keyphrases from the candidate set. SEERLAB achieved a 0.24 F-score in generating the top 15 keyphrases, which places it sixt...