For many languages that use non-Roman based indigenous scripts (e.g., Arabic, Greek and Indic languages) one can often find a large amount of user generated transliterated content on the Web in Roman script. Such creates monolingual or multi-lingual space with more than script which we refer to as Mixed-Script space. IR mixed-script is challenging because queries written either native need be matched documents both scripts. Moreover, features extensive spelling variations. In this paper,...

Using implicit feedback collected from user clicks as training labels for learning-to-rank algorithms is a well-developed paradigm that has been extensively studied and used in modern IR systems. ranking features, on the other hand, not fully explored existing literature. Despite its potential improving short-term system performance, whether incorporation of features beneficial systems long term still questionable. Two most important problems are (1) explicit bias introduced by noisy...

This paper presents a new hybrid and parallel processing image fusion technique for multi-focus images. Here, two different methods are used i.e. Stationary Wavelet Transform (SWT) Principal Component Analysis (PCA) that implemented on the input images in parallel. These applied same dataset. method is although computationally bit slower than compared but still it shows better results. The fused obtained from SWT PCA later again using method. technique. result of proposed with other...

Ranking is at the core of many artificial intelligence (AI) applications, including search engines, recommender systems, etc. Modern ranking systems are often constructed with learning-to-rank (LTR) models built from user behavior signals. While previous studies have demonstrated effectiveness using signals (e.g., clicks) as both features and labels LTR algorithms, we argue that existing algorithms indiscriminately treat non-behavior in input could lead to suboptimal performance practice....

The automatic alignment of documents in a quasi-comparable corpus is an important research problem for resource poor cross-language technologies. News stories form one the most prolific and abundant language resource. [email protected] task, !ndia news story search (CL!NSS), aimed to address linking task across languages English Hindi. We present overview track with results analysis.

Abstract Farmers in dryland regions are highly vulnerable to rainfall variability. This vulnerability is unequal, as it mediated by biophysical and social factors. Implementing policies for climate resilience requires identification of farmers who most extreme events like dry spells. We develop a novel approach conceptualizing spell at the farm scale terms monsoon crop water deficit. Using inputs weather, terrain, soil properties, land-use-land-cover, cadastral maps, our tool models an...

New products in e-commerce platforms suffer from cold start, both recommendation and search. In this study, we present experiments to deal with start search by predicting priors for behavioral features learning rank set up. The offline results show that our technique generates which closely track posterior values. online A/B test on 140MM queries shows treatment improves new impressions increased customers engagement pointing their relevance quality.

En los ultimos anos ha habido importantes avances en el campo de la deteccion plagio automatica. Uno ellos es translingue, cual trata detectar entre documentos diferentes idiomas. La mayoria aproximaciones que existen para esta tarea hacen uso diccionarios estadisticos lidiar con las traducciones palabras documentos. Un diccionario estadistico nos proporciona, una palabra dada, lista posibles sus respectivas probabilidades. El objetivo este trabajo analizar rendimiento del red semantica...

Seasonality is an important dimension for relevance in e-commerce search. For example, a query jacket has different set of relevant documents winter than summer. optimal user experience, the search engines should incorporate seasonality product In this paper, we formally introduce concept seasonal relevance, define it and quantify using data from major store. our analyses, find 39% queries are highly seasonally to time would benefit handling ranking. We propose LogSR VelSR features capture...