Unsupervised Graph-based Rank Aggregation for Improved Retrieval

This paper presents a robust and comprehensive graph-based rank aggregation approach, used to combine results of isolated ranker models in retrieval tasks. The method follows an unsupervised scheme, which is independent of how the isolated ranks are formulated. Our approach is able to combine arbitrary models, defined in terms of different ranking criteria, such as those based on textual, image or hybrid content representations. We reformulate the ad-hoc retrieval problem as a document retrieval based on fusion graphs, which we propose as a new unified representation model capable of merging multiple ranks and expressing inter-relationships of retrieval results automatically. By doing so, we claim that the retrieval system can benefit from learning the manifold structure of datasets, thus leading to more effective results. Another contribution is that our graph-based aggregation formulation, unlike existing approaches, allows for encapsulating contextual information encoded from multiple ranks, which can be directly used for ranking, without further computations and post-processing steps over the graphs. Based on the graphs, a novel similarity retrieval score is formulated using an efficient computation of minimum common subgraphs. Finally, another benefit over existing approaches is the absence of hyperparameters. A comprehensive experimental evaluation was conducted considering diverse well-known public datasets, composed of textual, image, and multimodal documents. Performed experiments demonstrate that our method reaches top performance, yielding better effectiveness scores than state-of-the-art baseline methods and promoting large gains over the rankers being fused, thus demonstrating the successful capability of the proposal in representing queries based on a unified graph-based model of rank fusions

Applications of comparators in data processing systems

This paper shows practical examples of compound object comparators and the application of the theory in various fields related to data processing systems. One can also find the necessary theoretical background needed to understand the examples

The dimension of oppositeness : universal and typological aspects

Oppositeness, i.e. the relation between opposites or contraries or contradictories, has a fundamental role in human cognition. In the various domains of intellectual and psychological activity we find ordering schemas that are based, in one way or another, on the cognitive figure of oppositeness. It is therefore not surprising that the figure and its corresponding ordering schemas show their reflexes in the languages of the world. [...] We shall be dealing with oppositeness in the sense that a linguistically untrained native speaker, when asked what would be the opposite of 'long' can come up with some such answer as 'short', and likewise intuitively grasp the relation between 'man' and 'woman', 'corne' and 'go', 'up' and 'down', etc. Thinking that much of the vocabulary of a language is organized in such opposite pairs we must recognize that this is an important faculty, and we are curious to know how this is done, what are the underlying conceptual-cognitive structures and processes, and how they are encoded in the languages of the world. We shall leave out of consideration such oppositions as singular vs. plural. present vs. past, voiced vs. unvoiced, oppositions that the linguist states by means of a metalanguage which is itself derived from a concept of oppositeness as manifested by the examples which I gave earlier. Our approach will connect with earlier versions of the UNITYP framework. However, as a novel feature, and, hopefully, as an improvement, we shall apply some sort of a division of labor. We shall first try to reconstruct the conceptual-cognitive content of oppositeness and to keep it separate from the discussion of its reflexes in the individual languages. We shall find that a dimensional ordering of content in PARAMETERS and a continuum of TECHNIQUES is possible already on the conceptual-cognitive level. In order to keep it distinct from the level of linguistic encoding we shall use a separate terminology, graphically marked by capital 1etters

A sub-mW IoT-endnode for always-on visual monitoring and smart triggering

This work presents a fully-programmable Internet of Things (IoT) visual sensing node that targets sub-mW power consumption in always-on monitoring scenarios. The system features a spatial-contrast $128\mathrm{x}64$ binary pixel imager with focal-plane processing. The sensor, when working at its lowest power mode ($10\mu W$ at 10 fps), provides as output the number of changed pixels. Based on this information, a dedicated camera interface, implemented on a low-power FPGA, wakes up an ultra-low-power parallel processing unit to extract context-aware visual information. We evaluate the smart sensor on three always-on visual triggering application scenarios. Triggering accuracy comparable to RGB image sensors is achieved at nominal lighting conditions, while consuming an average power between $193\mu W$ and $277\mu W$, depending on context activity. The digital sub-system is extremely flexible, thanks to a fully-programmable digital signal processing engine, but still achieves 19x lower power consumption compared to MCU-based cameras with significantly lower on-board computing capabilities.Comment: 11 pages, 9 figures, submitteted to IEEE IoT Journa

Marking as judgment

An aspect of assessment which has received little attention compared with perennial concerns, such as standards or reliability, is the role of judgment in marking. This paper explores marking as an act of judgment, paying particular attention to the nature of judgment and the processes involved. It brings together studies which have explored marking from a psychological perspective for the purpose of critical discussion of the light they shed on each other and on the practice of marking. Later stages speculate on recent developments in psychology and neuroscience which may cast further light on educational assessment