We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

Nowadays, multi-label classification methods are increasingly required by modern applications, such as protein function classification, music categorization and semantic scene classification. This paper introduces the task of multi-label classification, organizes the sparse related literature into a structured presentation and performs comparative experimental results of certain multi-label classification methods. It also contributes the definition of concepts for the quantification of the multi-label nature of a data set.

/pdf/multi-label-classification-an-overview-3lubavw9dw.pdf

Multi-label classification: An overview

We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.

When is nearest neighbor meaningful

Global Land Cover (GLC) information is fundamental for environmental change studies, land resource management, sustainable development, and many other societal benefits. Although GLC data exists at spatial resolutions of 300 m and 1000 m, a 30 m resolution mapping approach is now a feasible option for the next generation of GLC products. Since most significant human impacts on the land system can be captured at this scale, a number of researchers are focusing on such products. This paper reports the operational approach used in such a project, which aims to deliver reliable data products. Over 10,000 Landsat-like satellite images are required to cover the entire Earth at 30 m resolution. To derive a GLC map from such a large volume of data necessitates the development of effective, efficient, economic and operational approaches. Automated approaches usually provide higher efficiency and thus more economic solutions, yet existing automated classification has been deemed ineffective because of the low classification accuracy achievable (typically below 65%) at global scale at 30 m resolution. As a result, an approach based on the integration of pixel- and object-based methods with knowledge (POK-based) has been developed. To handle the classification process of 10 land cover types, a split-and-merge strategy was employed, i.e. firstly each class identified in a prioritized sequence and then results are merged together. For the identification of each class, a robust integration of pixel-and object-based classification was developed. To improve the quality of the classification results, a knowledge-based interactive verification procedure was developed with the support of web service technology. The performance of the POK-based approach was tested using eight selected areas with differing landscapes from five different continents. An overall classification accuracy of over 80% was achieved. This indicates that the developed POK-based approach is effective and feasible for operational GLC mapping at 30 m resolution.

Global land cover mapping at 30 m resolution: A POK-based operational approach

The technology underlying text search engines has advanced dramatically in the past decade. The development of a family of new index representations has led to a wide range of innovations in index storage, index construction, and query evaluation. While some of these developments have been consolidated in textbooks, many specific techniques are not widely known or the textbook descriptions are out of date. In this tutorial, we introduce the key techniques in the area, describing both a core implementation and how the core can be enhanced through a range of extensions. We conclude with a comprehensive bibliography of text indexing literature.

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Inverted files for text search engines

Context Gamification seeks for improvement of the user’s engagement, motivation, and performance when carrying out a certain task, by means of incorporating game mechanics and elements, thus making that task more attractive Much research work has studied the application of gamification in software engineering for increasing the engagement and results of developers Objective The objective of this paper is to carry out a systematic mapping of the field of gamification in software engineering in an attempt to characterize the state of the art of this field identifying gaps and opportunities for further research Method We carried out a systematic mapping with a view to finding the primary studies in the existing literature, which were later classified and analyzed according to four criteria: the software process area addressed, the gamification elements used, the type of research method followed, and the type of forum in which they were published A subjective evaluation of the studies was also carried out to evaluate them in terms of methodology, empirical evidence, integration with the organization, and replicability Results As a result of the systematic mapping we found 29 primary studies, published between January 2011 and June 2014 Most of them focus on software development, and to a lesser extent, requirements, project management, and other support areas In the main, they consider very simple gamification mechanics such as points and badges, and few provide empirical evidence of the impact of gamification Conclusions Existing research in the field is quite preliminary, and more research effort analyzing the impact of gamification in SE would be needed Future research work should look at other game mechanics in addition to the basic ones and should tackle software process areas that have not been fully studied, such as requirements, project management, maintenance, or testing Most studies share a lack of methodological support that would make their proposals replicable in other settings The integration of gamification with an organization’s existing tools is also an important challenge that needs to be taken up in this field

Gamification in software engineering – A systematic mapping

https://www.dcc.uchile.cl/~gnavarro/ps/is13.2.pdf

Compact representation of Web graphs with extended functionality

This paper presents a Web graph representation based on a compact tree structure that takes advantage of large empty areas of the adjacency matrix of the graph. Our results show that our method is competitive with the best alternatives in the literature, offering a very good compression ratio (3.3---5.3 bits per link) while permitting fast navigation on the graph to obtain direct as well as reverse neighbors (2---15 microseconds per neighbor delivered). Moreover, it allows for extended functionality not usually considered in compressed graph representations.

/pdf/k2-trees-for-compact-web-graph-representation-1utrgw72qt.pdf

k2-Trees for Compact Web Graph Representation

We present a new variable-length encoding scheme for sequences of integers, Directly Addressable Codes (DACs), which enables direct access to any element of the encoded sequence without the need of any sampling method. Our proposal is a kind of implicit data structure that introduces synchronism in the encoded sequence without using asymptotically any extra space. We show some experiments demonstrating that the technique is not only simple, but also competitive in time and space with existing solutions in several applications, such as the representation of LCP arrays or high-order entropy-compressed sequences.

/pdf/dacs-bringing-direct-access-to-variable-length-codes-39k7zntw1n.pdf

DACs: Bringing direct access to variable-length codes

The inverted index supports efficient full-text searches on natural language text collections. It requires some extra space over the compressed text that can be traded for search speed. It is usually fast for single-word searches, yet phrase searches require more expensive intersections. In this article we introduce a different kind of index. It replaces the text using essentially the same space required by the compressed text alone (compression ratio around 35p). Within this space it supports not only decompression of arbitrary passages, but efficient word and phrase searches. Searches are orders of magnitude faster than those over inverted indexes when looking for phrases, and still faster on single-word searches when little space is available. Our new indexes are particularly fast at counting the occurrences of words or phrases. This is useful for computing relevance of words or phrases.We adapt self-indexes that succeeded in indexing arbitrary strings within compressed space to deal with large alphabets. Natural language texts are then regarded as sequences of words, not characters, to achieve word-based self-indexes. We design an architecture that separates the searchable sequence from its presentation aspects. This permits applying case folding, stemming, removing stopwords, etc. as is usual on inverted indexes.

/pdf/word-based-self-indexes-for-natural-language-text-rbd891cn7c.pdf

Nieves R. Brisaboa

Papers

Gamification in software engineering – A systematic mapping

Compact representation of Web graphs with extended functionality

k2-Trees for Compact Web Graph Representation

DACs: Bringing direct access to variable-length codes

Word-based self-indexes for natural language text