OpenRaiser/Intern-Atlas huggingface dataset:
A framework: Cluster detection and multidimensional visualization of automated data mining using intelligent agents
Venue: arXiv cs.AI 2012
Year: 2012

Data Mining techniques plays a vital role like extraction of required knowledge, finding unsuspected information to make strategic decision in a novel way which in term understandable by domain experts. A generalized frame work is proposed by considering non - domain experts during mining process for better understanding, making better decision and better finding new patters in case of selecting suitable data mining techniques based on the user profile by means of intelligent agents. KEYWORDS: Data Mining Techniques, Intelligent Agents, User Profile, Multidimensional Visualization, Knowledge Discovery.
Packet Score based network security and Traffic Optimization
Venue: arXiv cs.NI 2012
Year: 2012

One of the critical threat to internet security is Distributed Denial of Service (DDoS). This paper by the introduction of automated online attack classification and attack packet discarding helps to resolve the network security issue by certain level. The incoming packets are assigned scores based on the priority associated with the attributes and on comparison with probability distribution of arriving packets on per packet basis.
Coded Cooperative Data Exchange Problem for General Topologies
Venue: arXiv cs.IT 2012
Year: 2012

We consider the "coded cooperative data exchange problem" for general graphs. In this problem, given a graph G=(V,E) representing clients in a broadcast network, each of which initially hold a (not necessarily disjoint) set of information packets; one wishes to design a communication scheme in which eventually all clients will hold all the packets of the network. Communication is performed in rounds, where in each round a single client broadcasts a single (possibly encoded) information packet to its neighbors in G. The objective is to design a broadcast scheme that satisfies all clients with the minimum number of broadcast rounds. The coded cooperative data exchange problem has seen significant research over the last few years; mostly when the graph G is the complete broadcast graph in which each client is adjacent to all other clients in the network, but also on general topologies, both in the fractional and integral setting. In this work we focus on the integral setting in general undirected topologies G. We tie the data exchange problem on G to certain well studied combinatorial properties of G and in such show that solving the problem exactly or even approximately within a multiplicative factor of \log{|V|} is intractable (i.e., NP-Hard). We then turn to study efficient data exchange schemes yielding a number of communication rounds comparable to our intractability result. Our communication schemes do not involve encoding, and in such yield bounds on the "coding advantage" in the setting at hand.
The number of Euler tours of a random directed graph
Venue: arXiv cs.DM 2012
Year: 2012

In this paper we obtain the expectation and variance of the number of Euler tours of a random Eulerian directed graph with fixed out-degree sequence. We use this to obtain the asymptotic distribution of the number of Euler tours of a random $d$-in/$d$-out graph and prove a concentration result. We are then able to show that a very simple approach for uniform sampling or approximately counting Euler tours yields algorithms running in expected polynomial time for almost every $d$-in/$d$-out graph. We make use of the BEST theorem of de Bruijn, van Aardenne-Ehrenfest, Smith and Tutte, which shows that the number of Euler tours of an Eulerian directed graph with out-degree sequence $\mathbf{d}$ is the product of the number of arborescences and the term $\frac{1}{n}[\prod_{v \in V}(d_v-1)!]$. Therefore most of our effort is towards estimating the moments of the number of arborescences of a random graph with fixed out-degree sequence.
The Groupon Effect on Yelp Ratings: A Root Cause Analysis
Venue: arXiv cs.SI 2012
Year: 2012

Daily deals sites such as Groupon offer deeply discounted goods and services to tens of millions of customers through geographically targeted daily e-mail marketing campaigns. In our prior work we observed that a negative side effect for merchants using Groupons is that, on average, their Yelp ratings decline significantly. However, this previous work was essentially observational, rather than explanatory. In this work, we rigorously consider and evaluate various hypotheses about underlying consumer and merchant behavior in order to understand this phenomenon, which we dub the Groupon effect. We use statistical analysis and mathematical modeling, leveraging a dataset we collected spanning tens of thousands of daily deals and over 7 million Yelp reviews. In particular, we investigate hypotheses such as whether Groupon subscribers are more critical than their peers, or whether some fraction of Groupon merchants provide significantly worse service to customers using Groupons. We suggest an additional novel hypothesis: reviews from Groupon subscribers are lower on average because such reviews correspond to real, unbiased customers, while the body of reviews on Yelp contain some fraction of reviews from biased or even potentially fake sources. Although we focus on a specific question, our work provides broad insights into both consumer and merchant behavior within the daily deals marketplace.
Sum-Rate Maximization in Two-Way AF MIMO Relaying: Polynomial Time Solutions to a Class of DC Programming Problems
Venue: arXiv cs.IT 2012
Year: 2012

Sum-rate maximization in two-way amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying belongs to the class of difference-of-convex functions (DC) programming problems. DC programming problems occur as well in other signal processing applications and are typically solved using different modifications of the branch-and-bound method. This method, however, does not have any polynomial time complexity guarantees. In this paper, we show that a class of DC programming problems, to which the sum-rate maximization in two-way MIMO relaying belongs, can be solved very efficiently in polynomial time, and develop two algorithms. The objective function of the problem is represented as a product of quadratic ratios and parameterized so that its convex part (versus the concave part) contains only one (or two) optimization variables. One of the algorithms is called POlynomial-Time DC (POTDC) and is based on semi-definite programming (SDP) relaxation, linearization, and an iterative search over a single parameter. The other algorithm is called RAte-maximization via Generalized EigenvectorS (RAGES) and is based on the generalized eigenvectors method and an iterative search over two (or one, in its approximate version) optimization variables. We also derive an upper-bound for the optimal values of the corresponding optimization problem and show by simulations that this upper-bound can be achieved by both algorithms. The proposed methods for maximizing the sum-rate in the two-way AF MIMO relaying system are shown to be superior to other state-of-the-art algorithms.
DEPAS: A Decentralized Probabilistic Algorithm for Auto-Scaling
Venue: arXiv cs.DC 2012
Year: 2012

The dynamic provisioning of virtualized resources offered by cloud computing infrastructures allows applications deployed in a cloud environment to automatically increase and decrease the amount of used resources. This capability is called auto-scaling and its main purpose is to automatically adjust the scale of the system that is running the application to satisfy the varying workload with minimum resource utilization. The need for auto-scaling is particularly important during workload peaks, in which applications may need to scale up to extremely large-scale systems. Both the research community and the main cloud providers have already developed auto-scaling solutions. However, most research solutions are centralized and not suitable for managing large-scale systems, moreover cloud providers' solutions are bound to the limitations of a specific provider in terms of resource prices, availability, reliability, and connectivity. In this paper we propose DEPAS, a decentralized probabilistic auto-scaling algorithm integrated into a P2P architecture that is cloud provider independent, thus allowing the auto-scaling of services over multiple cloud infrastructures at the same time. Our simulations, which are based on real service traces, show that our approach is capable of: (i) keeping the overall utilization of all the instantiated cloud resources in a target range, (ii) maintaining service response times close to the ones obtained using optimal centralized auto-scaling approaches.
A Comprehensive Study of Commonly Practiced Heavy & Light Weight Software Methodologies
Venue: arXiv cs.SE 2012
Year: 2012

Software has been playing a key role in the development of modern society. Software industry has an option to choose suitable methodology/process model for its current needs to provide solutions to give problems. Though some companies have their own customized methodology for developing their software but majority agrees that software methodologies fall under two categories that are heavyweight and lightweight. Heavyweight methodologies (Waterfall Model, Spiral Model) are also known as the traditional methodologies, and their focuses are detailed documentation, inclusive planning, and extroverted design. Lightweight methodologies (XP, SCRUM) are, referred as agile methodologies. Light weight methodologies focused mainly on short iterative cycles, and rely on the knowledge within a team. The aim of this paper is to describe the characteristics of popular heavyweight and lightweight methodologies that are widely practiced in software industries. We have discussed the strengths and weakness of the selected models. Further we have discussed the strengths and weakness between the two opponent methodologies and some criteria is also illustrated that help project managers for the selection of suitable model for their projects.
Using Covariance Matrices as Feature Descriptors for Vehicle Detection from a Fixed Camera
Venue: arXiv cs.CV 2012
Year: 2012

A method is developed to distinguish between cars and trucks present in a video feed of a highway. The method builds upon previously done work using covariance matrices as an accurate descriptor for regions. Background subtraction and other similar proven image processing techniques are used to identify the regions where the vehicles are most likely to be, and a distance metric comparing the vehicle inside the region to a fixed library of vehicles is used to determine the class of vehicle.
Data Dissemination in Opportunistic Networks
Venue: arXiv cs.NI 2012
Year: 2012

Mobile devices integrating wireless short-range communication technologies make possible new applications for spontaneous communication, interaction and collaboration. An interesting approach is to use collaboration to facilitate communication when mobile devices are not able to establish direct communication paths. Opportunistic networks, formed when mobile devices communicate with each other while users are in close proximity, can help applications still exchange data in such cases. In opportunistic networks routes are built dynamically, as each mobile device acts according to the store-carry-and-forward paradigm. Thus, contacts between mobile devices are seen as opportunities to move data towards destination. In such networks data dissemination is done using forwarding and is usually based on a publish/subscribe model. Opportunistic data dissemination also raises questions concerning user privacy and incentives. Such problems are addressed differently by various opportunistic data dissemination techniques. In this paper we analyze existing relevant work in the area of data dissemination in opportunistic networks. We present the categories of a proposed taxonomy that captures the capabilities of data dissemination techniques used in such networks. Moreover, we survey relevant data dissemination techniques and analyze them using the proposed taxonomy.
Revolutionaries and spies: Spy-good and spy-bad graphs
Venue: arXiv cs.DM 2012
Year: 2012

We study a game on a graph $G$ played by $r$ {\it revolutionaries} and $s$ {\it spies}. Initially, revolutionaries and then spies occupy vertices. In each subsequent round, each revolutionary may move to a neighboring vertex or not move, and then each spy has the same option. The revolutionaries win if $m$ of them meet at some vertex having no spy (at the end of a round); the spies win if they can avoid this forever. Let $σ(G,m,r)$ denote the minimum number of spies needed to win. To avoid degenerate cases, assume $|V(G)|\ge r-m+1\ge\floor{r/m}\ge 1$. The easy bounds are then $\floor{r/m}\le σ(G,m,r)\le r-m+1$. We prove that the lower bound is sharp when $G$ has a rooted spanning tree $T$ such that every edge of $G$ not in $T$ joins two vertices having the same parent in $T$. As a consequence, $σ(G,m,r)\leγ(G)\floor{r/m}$, where $γ(G)$ is the domination number; this bound is nearly sharp when $γ(G)\le m$. For the random graph with constant edge-probability $p$, we obtain constants $c$ and $c'$ (depending on $m$ and $p$) such that $σ(G,m,r)$ is near the trivial upper bound when $r<c\ln n$ and at most $c'$ times the trivial lower bound when $r>c'\ln n$. For the hypercube $Q_d$ with $d\ge r$, we have $σ(G,m,r)=r-m+1$ when $m=2$, and for $m\ge 3$ at least $r-39m$ spies are needed. For complete $k$-partite graphs with partite sets of size at least $2r$, the leading term in $σ(G,m,r)$ is approximately $\frac{k}{k-1}\frac{r}{m}$ when $k\ge m$. For $k=2$, we have $σ(G,2,r)=\bigl\lceil{\frac{\floor{7r/2}-3}5}\bigr\rceil$ and $σ(G,3,r)=\floor{r/2}$, and in general $\frac{3r}{2m}-3\le σ(G,m,r)\le\frac{(1+1/\sqrt3)r}{m}$.
Randomization Resilient To Sensitive Reconstruction
Venue: arXiv cs.DB 2012
Year: 2012

With the randomization approach, sensitive data items of records are randomized to protect privacy of individuals while allowing the distribution information to be reconstructed for data analysis. In this paper, we distinguish between reconstruction that has potential privacy risk, called micro reconstruction, and reconstruction that does not, called aggregate reconstruction. We show that the former could disclose sensitive information about a target individual, whereas the latter is more useful for data analysis than for privacy breaches. To limit the privacy risk of micro reconstruction, we propose a privacy definition, called (epsilon,delta)-reconstruction-privacy. Intuitively, this privacy notion requires that micro reconstruction has a large error with a large probability. The promise of this approach is that micro reconstruction is more sensitive to the number of independent trials in the randomization process than aggregate reconstruction is; therefore, reducing the number of independent trials helps achieve (epsilon,delta)-reconstruction-privacy while preserving the accuracy of aggregate reconstruction. We present an algorithm based on this idea and evaluate the effectiveness of this approach using real life data sets.
Greedy Sequential Maximal Independent Set and Matching are Parallel on Average
Venue: arXiv cs.DS 2012
Year: 2012

The greedy sequential algorithm for maximal independent set (MIS) loops over the vertices in arbitrary order adding a vertex to the resulting set if and only if no previous neighboring vertex has been added. In this loop, as in many sequential loops, each iterate will only depend directly on a subset of the previous iterates (i.e. knowing that any one of a vertices neighbors is in the MIS or knowing that it has no previous neighbors is sufficient to decide its fate). This leads to a dependence structure among the iterates. If this structure is shallow then running the iterates in parallel while respecting the dependencies can lead to an efficient parallel implementation mimicking the sequential algorithm. In this paper, we show that for any graph, and for a random ordering of the vertices, the dependence depth of the sequential greedy MIS algorithm is polylogarithmic (O(log^2 n) with high probability). Our results extend previous results that show polylogarithmic bounds only for random graphs. We show similar results for a greedy maximal matching (MM). For both problems we describe simple linear work parallel algorithms based on the approach. The algorithms allow for a smooth tradeoff between more parallelism and reduced work, but always return the same result as the sequential greedy algorithms. We present experimental results that demonstrate efficiency and the tradeoff between work and parallelism.
Small Count Privacy and Large Count Utility in Data Publishing
Venue: arXiv cs.DB 2012
Year: 2012

While the introduction of differential privacy has been a major breakthrough in the study of privacy preserving data publication, some recent work has pointed out a number of cases where it is not possible to limit inference about individuals. The dilemma that is intrinsic in the problem is the simultaneous requirement of data utility in the published data. Differential privacy does not aim to protect information about an individual that can be uncovered even without the participation of the individual. However, this lack of coverage may violate the principle of individual privacy. Here we propose a solution by providing protection to sensitive information, by which we refer to the answers for aggregate queries with small counts. Previous works based on $\ell$-diversity can be seen as providing a special form of this kind of protection. Our method is developed with another goal which is to provide differential privacy guarantee, and for that we introduce a more refined form of differential privacy to deal with certain practical issues. Our empirical studies show that our method can preserve better utilities than a number of state-of-the-art methods although these methods do not provide the protections that we provide.
Service Composition in Service-Oriented Wireless Sensor Networks with Persistent Queries
Venue: arXiv cs.NI 2012
Year: 2012

Service-oriented wireless sensor network(WSN) has been recently proposed as an architecture to rapidly develop applications in WSNs. In WSNs, a query task may require a set of services and may be carried out repetitively with a given frequency during its lifetime. A service composition solution shall be provided for each execution of such a persistent query task. Due to the energy saving strategy, some sensors may be scheduled to be in sleep mode periodically. Thus, a service composition solution may not always be valid during the lifetime of a persistent query. When a query task needs to be conducted over a new service composition solution, a routing update procedure is involved which consumes energy. In this paper, we study service composition design which minimizes the number of service composition solutions during the lifetime of a persistent query. We also aim to minimize the total service composition cost when the minimum number of required service composition solutions is derived. A greedy algorithm and a dynamic programming algorithm are proposed to complete these two objectives respectively. The optimality of both algorithms provides the service composition solutions for a persistent query with minimum energy consumption.
Speeding-up $q$-gram mining on grammar-based compressed texts
Venue: arXiv cs.DS 2012
Year: 2012

We present an efficient algorithm for calculating $q$-gram frequencies on strings represented in compressed form, namely, as a straight line program (SLP). Given an SLP $\mathcal{T}$ of size $n$ that represents string $T$, the algorithm computes the occurrence frequencies of all $q$-grams in $T$, by reducing the problem to the weighted $q$-gram frequencies problem on a trie-like structure of size $m = |T|-\mathit{dup}(q,\mathcal{T})$, where $\mathit{dup}(q,\mathcal{T})$ is a quantity that represents the amount of redundancy that the SLP captures with respect to $q$-grams. The reduced problem can be solved in linear time. Since $m = O(qn)$, the running time of our algorithm is $O(\min\{|T|-\mathit{dup}(q,\mathcal{T}),qn\})$, improving our previous $O(qn)$ algorithm when $q = Ω(|T|/n)$.
Lattices of Logical Fragments over Words
Venue: arXiv cs.FL 2012
Year: 2012

This paper introduces an abstract notion of fragments of monadic second-order logic. This concept is based on purely syntactic closure properties. We show that over finite words, every logical fragment defines a lattice of languages with certain closure properties. Among these closure properties are residuals and inverse C-morphisms. Here, depending on certain closure properties of the fragment, C is the family of arbitrary, non-erasing, length-preserving, length-multiplying, or length-reducing morphisms. In particular, definability in a certain fragment can often be characterized in terms of the syntactic morphism. This work extends a result of Straubing in which he investigated certain restrictions of first-order logic formulae. In contrast to Straubing's model-theoretic approach, our notion of a logical fragment is purely syntactic and it does not rely on Ehrenfeucht-Fraisse games. As motivating examples, we present (1) a fragment which captures the stutter-invariant part of piecewise-testable languages and (2) an acyclic fragment of Sigma_2. As it turns out, the latter has the same expressive power as two-variable first-order logic FO^2.
Faster Approximate Multicommodity Flow Using Quadratically Coupled Flows
Venue: arXiv cs.DS 2012
Year: 2012

The maximum multicommodity flow problem is a natural generalization of the maximum flow problem to route multiple distinct flows. Obtaining a $1-ε$ approximation to the multicommodity flow problem on graphs is a well-studied problem. In this paper we present an adaptation of recent advances in single-commodity flow algorithms to this problem. As the underlying linear systems in the electrical problems of multicommodity flow problems are no longer Laplacians, our approach is tailored to generate specialized systems which can be preconditioned and solved efficiently using Laplacians. Given an undirected graph with m edges and k commodities, we give algorithms that find $1-ε$ approximate solutions to the maximum concurrent flow problem and the maximum weighted multicommodity flow problem in time $\tilde{O}(m^{4/3}\poly(k,ε^{-1}))$.
Towards Maximum Spanning Tree Model in Web 3.0 Design and Development for Students using Discriminant Analysis
Venue: arXiv cs.OH 2012
Year: 2012

Web 3.0 is an evolving extension of the web 2.0 scenario. The perceptions regarding web 3.0 is different from person to person . Web 3.0 Architecture supports ubiquitous connectivity, network computing, open identity, intelligent web, distributed databases and intelligent applications. Some of the technologies which lead to the design and development of web 3.0 applications are Artificial intelligence, Automated reasoning, Cognitive architecture, Semantic web . An attempt is made to capture the requirements of Students inline with web 3.0 so as to bridge the gap between the design and development of web 3.0 applications and requirements among Students. Maximum Spanning Tree modeling of the requirements facilitate the identification of key areas and key attributes in the design and development of software products for Students in Web 3.0 using Discriminant analysis. Keywords : Web 3.0, Discriminant analysis, Design and Development, Model, Maximum Spanning Tree 1.