Text readability is typically defined in terms of “grade level”; the expected educational level of the reader at which the text is directed. Mechanisms for measuring readability in English documents are well established; however this is not in case in many other languages, such as syllabic alphabetic languages. In this paper seven different mechanisms for assessing the readability of syllabic a...

Different flip-flop designs vary in the number and complexity of logic stages they contain, and hence have different inherent parasitic delays and output drive strengths. We examine the effect of electrical load on flip-flop delay and energy consumption and show that the relative ranking of optimized flip-flop structures varies widely with both electrical effort and absolute load. We also show ...

The web is a vast repository of information. Most of the information on the web is meant for human consumption. Extracting structured information from the web can enable several applications like advanced ranking, semantic search, etc. In this talk, we first list different types of content available on the web, survey known techniques for extracting information from them, present the architectu...

Aggregate ranking tasks are those where documents are not the final ranking outcome, but instead an intermediary component. For instance, in expert search, a ranking of candidate persons with relevant expertise to a query is generated after consideration of a document ranking. Many models exist for aggregate ranking tasks, however obtaining an effective and robust setting for different aggregat...

This paper provides an overview of the NTCIR-10 INTENT-2 task (the second INTENT task), which comprises the Subtopic Mining and the Document Ranking subtasks. INTENT-2 attracted participating teams from China, France, Japan and South Korea – 12 teams for Subtopic Mining and 4 teams for Document Ranking (including an organisers’ team). The Subtopic Mining subtask received 34 English runs, 23 Chi...

Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly applied to all queries, many studies have shown that different ranking functions favour different queries, and the retrieval performance can be significantly enhanced if an appropriate ranking function is selected for each indi...

Measuring the quality of life in municipalities entails two empirical challenges. First, collecting a set of relevant indicators that can be compared across the municipalities. Second, using an appropriate aggregating tool in order to construct a synthetic index. This paper measures the quality of life for the largest 643 Spanish municipalities using Value Efficiency Analysis (VEA). The indicat...

Ranking-aware queries, or top-k queries, have received much attention recently in various contexts such as web, multimedia retrieval, relational databases, and distributed systems. Top-k queries play a critical role in many decision-making related activities such as, identifying interesting objects, network monitoring, load balancing, etc. In this paper, we study the ranking aggregation problem...

Similarity calculations and document ranking form the computationally expensive parts of query processing in ranking-based text retrieval. In this work, for these calculations, 11 alternative implementation techniques are presented under four different categories, and their asymptotic time and space complexities are investigated. To our knowledge, six of these techniques are not discussed in an...