ppxscal/embedding_network huggingface dataset:
Discovering Sentinel Rules for Business Intelligence
Authors: Morten Middelfart, Torben Bach Pedersen
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

This paper proposes the concept of sentinel rules for multi-dimensional data that warns users when measure data concerning the external environment changes. For instance, a surge in negative blogging about a company could trigger a sentinel rule warning that revenue will decrease within two months, so a new course of action can be taken. Hereby, we expand the window of opportunity for organizations and facilitate successful navigation even though the world behaves chaotically. Since sentinel rules are at the schema level as opposed to the data level, and operate on data changes as opposed to absolute data values, we are able to discover strong and useful sentinel rules that would otherwise be hidden when using sequential pattern mining or correlation techniques. We present a method for sentinel rule discovery and an implementation of this method that scales linearly on large data volumes.
The Model and Strategy of Knowledge Transfer in Project Environments
Authors: Yang Tong, Wang Nengmin
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

Enhancing project knowledge management can effectively shorten the project schedule and reduce costs, improve quality and consumer satisfaction. Effective knowledge transfer project are an important way to eliminate amnesia. This paper analyzes the characteristics of knowledge transfer, based on this through combination of knowledge management theory exploring the process model of knowledge transfer and characteristics of knowledge transfer among project. Finally, it discusses how to improve inter-project knowledge transfer efficiency.
Relay node placement in large scale wireless sensor networks
Authors: Jian Tang, Bin Hao, Arunabha Sen
Venue: Computer Communications (2006)

Scalability and extended lifetime are two critical design goals of any large scale wireless sensor network. A two-tiered network model has been proposed recently for this purpose. This is a cluster-based network model composed of relay and sensor nodes. Relay nodes are placed in the playing field to serve as cluster heads and to form a connected network topology for information dissemination at the higher tier. The relay nodes are capable of aggregating data packets from the sensor nodes in their clusters and transmitting them to the sink node via wireless multi-hop paths. In this paper, we study the relay node placement problem in large scale wireless sensor networks. Our objective is to place the fewest number of relay nodes in the playing field of a sensor network such that (1) each sensor node can communicate with at least one relay node and (2) the network of relay nodes is connected. However, placement strategies realizing goals (1) and (2) do not provide any fault-tolerance as the network may lose functionality after failure of some of the relay nodes. In order to incorporate fault-tolerance in such a network, we ensure that every sensor node is able to communicate with at least two relay nodes and the induced network topology is 2-connected. This strategy will ensure survivability of the network in the event of single fault, in lieu of higher relay node placement cost. We formulate the relay node placement in wireless sensor networks as two optimization problems: (i) Connected Relay Node Single Cover (CRNSC) problem and (ii) 2-Connected Relay Node Double Cover (2CRNDC) problem. We present two polynomial time approximation algorithms to solve the CRNSC problem. We prove that the ratio of the number of relay nodes needed by the approximation algorithm to the number of relay nodes needed by the optimal algorithm is bounded by 8 for the first algorithm and 4.5 for the second. In addition, for the 2CRNDC problem we provide two approximation algorithms with performance bounds 6 and 4.5, respectively.
Conditional confidence intervals for classification error rate
Authors: Hie-Choon Chung, Chien-Pai Han
Venue: Computational Statistics Data Analysis (2009)

An observation is to be classified into one of several multivariate normal populations with equal covariance matrix. When the parameters are unknown, independent training samples are taken from the populations. We consider the construction of confidence intervals for the conditional error rate. The cases of two populations and three populations are studied in detail. We propose the conditional jackknife confidence interval and the conditional bootstrap confidence intervals of the conditional error rate. A Monte Carlo study is conducted to compare the confidence intervals.
Multi-component tree adjoining grammars, dependency graph models, and linguistic analyses
Authors: Joan Chen-Main, Aravind K. Joshi
Venue: Proceedings of the Workshop on Deep Linguistic Processing (2007)

Recent work identifies two properties that appear particularly relevant to the characterization of graph-based dependency models of syntactic structure: the absence of interleaving substructures (well-nestedness) and a bound on a type of discontinuity (gap-degree &le; 1) successfully describe more than 99% of the structures in two dependency treebanks (Kuhlmann and Nivre 2006). Bodirsky et al. (2005) establish that every dependency structure with these two properties can be recast as a lexicalized Tree Adjoining Grammar (LTAG) derivation and vice versa. However, multi-component extensions of TAG (MC-TAG), argued to be necessary on linguistic grounds, induce dependency structures that do not conform to these two properties (Kuhlmann and M&ouml;hl 2006). In this paper, we observe that several types of MC-TAG as used for linguistic analysis are more restrictive than the formal system is in principle. In particular, tree-local MC-TAG, tree-local MC-TAG with flexible composition (Kallmeyer and Joshi 2003), and special cases of set-local TAG as used to describe certain linguistic phenomena satisfy the well-nested and gap degree &le; 1 criteria. We also observe that gap degree can distinguish between prohibited and allowed wh-extractions in English, and report some preliminary work comparing the predictions of the graph approach and the MC-TAG approach to scrambling.
An expressive auction design for online display advertising
Authors: Sébastien Lahaie, David C. Parkes, David M. Pennock
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

We propose an expressive auction design that allows advertisers to specify the kinds of demographics and websites they wish to target within an advertising network. The design allows the network to differentiate impressions according to relevant attributes (e.g., geographic location of the user, topic of the webpage). Advertisers can place bids for different kinds of impressions according to their attributes, and can also specify volume constraints to control exposure. The novelty of the design is a bidding language that admits scalable allocation and pricing algorithms. We discuss the incentive properties of different pricing approaches. We also propose a bidder feedback mechanism to mitigate the complexity of expressive bidding.
Multiple Round Random Ball Placement: Power of Second Chance
Authors: Xiang-Yang Li, Yajun Wang, Wangsen Feng
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

The traditional coupon collector's problem studies the number of balls required to fill n bins if the balls are placed into bins uniformly at random. It is folklore that ¿(nln n) balls are required to fill the bins with high probability (w.h.p.). In this paper, we study a variation of the random ball placement process. In each round, we assume the ability to acquire the set of empty bins after previous rounds and exclusively place balls into them uniformly at random. For such a k-round random ball placement process (k -RBP), we derive a sharp threshold of nln [k] n balls for filling n bins.We apply the bounds of k -RBP to the wireless sensor network deployment problem. Assume the communication range for the sensors is r and the deployment region is a 2D unit square. Let n = (1/r)2. We show that the number of random nodes needed to achieve connectivity is ¿(nln ln n) if we are given a "second chance" to deploy nodes, improving the previous ¿(nln n) bounds [8] in the one round case. More generally, under certain deployment assumption, if the random deployment in i-th round can utilize the information from the previous i ¿ 1 rounds, the asymptotic number of nodes to satisfy connectivity is ¿(n ln [k] n) for k rounds. Similar results also hold if the sensing regions of the deployed nodes are required to cover the region of interest.
Comparative Study of Some Improved ANN-Models for Hydrologic Time Series Forecast
Authors: Sang Yanfang, Wang Dong, Wu Jichun
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

In this paper, by taking two real hydrologic series for examples, the performances of some improved ANN-models (including BPNN, gda-BPNN, gdm-BPNN, gdx-BPNN, LM-BPNN, WANN and WNN) have been discussed and compared. Analysis results show that: 1) Among all BPNN-models, gdx-BP, gda-BP, gdm-BP and LM-BP are better than standard BPNN, and gda-BP and gdm-BP are the most satisfying; 2) Compared with BPNN-models, WANN and WNN models are much better especially when hydrologic series are very complex and more long forecast periods are needed, since they can take great advantages of multi-resolution analysis ability of WA; and 3) WANN model has many advantages, such as can understand internal structure and characters of series meanwhile, high forecast accuracy, high eligible rate, can overcome the contradiction between high accuracy and long forecast period, etc. Although WANN and WNN models can meet almost all practical needs, some key and difficult problems about them should be solved furthermore.
Analytic drawing of 3D scaffolds
Authors: Ryan Schmidt, Azam Khan, Karan Singh, Gord Kurtenbach
Venue: ACM SIGGRAPH Asia 2009 papers (2009)

We describe a novel approach to inferring 3D curves from perspective drawings in an interactive design tool. Our methods are based on a traditional design drawing style known as analytic drawing, which supports precise image-space construction of a linear 3D scaffold. This scaffold in turn acts as a set of visual constraints for sketching 3D curves. We implement analytic drawing techniques in a pure-inference sketching interface which supports both single-and multi-view incremental construction of complex scaffolds and curve networks. A new representation of 3D drawings is proposed, and useful interactive drawing aids are described. Novel techniques are presented for deriving constraints from single-view sketches drawn relative to the current 3D scaffold, and then inferring 3D line and curve geometry which satisfies these constraints. The resulting analytic drawing tool allows 3D drawings to be constructed using exactly the same strokes as one would make on paper.
Satisfying market demands with delivery obligations or delivery charges
Authors: Yongjun Xiao, Kevin Taaffe
Venue: Computers and Operations Research (2010)

Consider a firm that receives deterministic, time-varying demands for its product. The firm has the flexibility to choose its customer base and receive market-specific revenues for its product. In addition to market revenue and market demand, the parameters of a negotiated contract can also play a role in market selection and fulfillment decisions. Two such parameters are (1) delivery obligation penalties and (2) delivery charges. In this paper, we determine optimal solution approaches for problem settings when either of these contract parameters is present. Our tailored solution techniques can solve each problem in a fraction of the time required by a state-of-the-art commercial optimization solver.
A Story Authoring System for Children
Authors: Danli Wang, Tingting Yin, Fang Peng, Jinquan Xiong, Hongan Wang, Guozhong Dai
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

Storytelling is a practical and powerful tool for children to develop their language expression and creativity. Many researchers have studied and built storytelling systems for children. Based on the analysis on the existing work, we designed and developed a 3D story authoring system for children by using pen/speech-based multimodal interaction technology. The system allows children to create roles, design roles' actions, make and share their own stories. The aim of this system is to cultivate the imagination and creativity of children, and to improve their language expression.
Consensus Optimizing Both Distance Sum and Radius
Authors: Amihood Amir, Gad M. Landau, Joong Chae Na, Heejin Park, Kunsoo Park, Jeong Seop Sim
Venue: Proceedings of the 16th International Symposium on String Processing and Information Retrieval (2009)

The consensus string problem is finding a representative string (consensus) of a given set $\mathbb{S}$ of strings. In this paper we deal with the consensus string problems optimizing both distance sum and radius, where the distance sum is the sum of (Hamming) distances from the strings in $\mathbb{S}$ to the consensus and the radius is the longest (Hamming) distance from the strings in $\mathbb{S}$ to the consensus. Although there have been results considering either distance sum or radius, there have been no results considering both as far as we know.We present two algorithms to solve the consensus string problems optimizing both distance sum and radius for three strings. The first algorithm finds the optimal consensus string that minimizes both distance sum and radius, and the second algorithm finds the bounded consensus string such that, given constants s and r, the distance sum is at most s and the radius is at most r. Both algorithms take linear time.
An evaluation understudy for dialogue coherence models
Authors: Sudeep Gandhe, David Traum
Venue: Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue (2008)

Evaluating a dialogue system is seen as a major challenge within the dialogue research community. Due to the very nature of the task, most of the evaluation methods need a substantial amount of human involvement. Following the tradition in machine translation, summarization and discourse coherence modeling, we introduce the the idea of evaluation understudy for dialogue coherence models. Following (Lapata, 2006), we use the information ordering task as a testbed for evaluating dialogue coherence models. This paper reports findings about the reliability of the information ordering task as applied to dialogues. We find that simple n-gram co-occurrence statistics similar in spirit to BLEU (Papineni et al., 2001) correlate very well with human judgments for dialogue coherence
Co-designing curricula to promote collaborative knowledge construction in secondary school science
Authors: Vanessa L. Peters, James D. Slotta
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

We describe a two-year study of a rich secondary science curriculum that was codesigned in close partnership with teachers, technology specialists and even school administrators. The goal of the research was to provide empirical support for a recent model of learning and instruction that blends the two perspectives of knowledge communities and scaffolded inquiry. A design-oriented method was employed, where the first iteration of the curriculum was evaluated in terms of its fit to the model, as well as its impact on student learning. Based on a set of design recommendations, a much more substantive curriculum was developed for the second iteration, leading to rich measures of student collaboration and deep understanding of the targeted science concepts. This paper describes our co-design process, which allowed teachers to lead the curriculum design and classroom enactment while researchers contributed design guidelines according to the theoretical model.
A Geographic Information Knowledge Discovery Model Based on Rough Set and Neural Network
Authors: Yannan Sun, Xiumei Li
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

The paper proposes a model based on rough set theory and neural network technology to discover knowledge from geographic information that has high spatial autocorrelation and fuzzy characteristics. In the model first get the most concise if-then rules by discernibility matrix. Then construct a three-layer neural network to simulate the most concise rules. Inputs and outputs of the neural network are determined by the parameter-training method that is provided in this paper. Finally the paper presents a simulation of its use for judging drought and flood disasters in Songliao River base. The results show that the model can quickly form the most concise rules and make right decision.
Computational Methods for Counterterrorism, 1st edition
Authors: Shlomo Argamon, Newton Howard
Venue:  (2009)

Modern terrorist networks pose an unprecedented threat to international security. The question of how to neutralize that threat is complicated radically by their fluid, non-hierarchical structures, religious and ideological motivations, and predominantly non-territorial objectives. Governments and militaries are crafting new policies and doctrines to combat terror, but they desperately need new technologies to make these efforts effective. This book collects a wide range of the most current computational research that addresses critical issues for countering terrorism, including: Finding, summarizing, and evaluating relevant information from large and changing data stores; Simulating and predicting enemy acts and outcomes; and Producing actionable intelligence by finding meaningful patterns hidden in huge amounts of noisy data. The books four sections describe current research on discovering relevant information buried in vast amounts of unstructured data; extracting meaningful information from digitized documents in multiple languages; analyzing graphs and networks to shed light on adversaries goals and intentions; and developing software systems that enable analysts to model, simulate, and predict the effects of real-world conflicts. The research described in this book is invaluable reading for governmental decision-makers designing new policies to counter terrorist threats, for members of the military, intelligence, and law enforcement communities devising counterterrorism strategies, and for researchers developing more effective methods for knowledge discovery in complicated and diverse datasets.
Interactive design of urban spaces using geometrical and behavioral modeling
Authors: Carlos A. Vanegas, Daniel G. Aliaga, Bedřich Beneš, Paul A. Waddell
Venue: ACM Transactions on Graphics (TOG) (2009)

The main contribution of our work is in closing the loop between behavioral and geometrical modeling of cities. Editing of urban design variables is performed intuitively and visually using a graphical user interface. Any design variable can be constrained or changed. The design process uses an iterative dynamical system for reaching equilibrium: a state where the demands of behavioral modeling match those of geometrical modeling. 3D models are generated in a few seconds and conform to plausible urban behavior and urban geometry. Our framework includes an interactive agent-based behavioral modeling system as well as adaptive geometry generation algorithms. We demonstrate interactive and incremental design and editing for synthetic urban spaces spanning over 200 square kilometers.
Building on the Usability Study: Two Explorations on How to Better Understand an Interface
Authors: Anshu Agarwal, Madhu Prabaker
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

In this paper, we describe two separate studies that improved our ability to understand our users' experience of our products at salesforce.com. The first study explored a methodology of combining expert and novice performance data to yield a measure of intuitiveness. The second study created a methodology that combines both verbal and nonverbal emotion scales to better understand the emotional effect our products have on our users. We present both these methods as expansions on the standard usability study and examples of ways to better understand your users within an industry environment.
Distributed parse mining
Authors: Scott A. Waterman
Venue: Proceedings of the Workshop on Software Engineering, Testing, and Quality Assurance for Natural Language Processing (2009)

We describe the design and implementation of a system for data exploration over dependency parses and derived semantic representations in a large-scale NLP-based search system at powerset.com. Because of the distributed nature of the document repository and the processing infrastructure, and also the complex representations of the corpus data, standard text analysis tools such as grep or awk or language modeling toolkits are not applicable. This paper explores the challenges of extracting statistical information and of building language models in such a distributed NLP environment, and introduces a corpus analysis system, Oceanography, that simplifies the writing of analysis code and transparently takes advantage of existing distributed processing infrastructure.
Ontology Component Development
Authors: Shenghong Yang, Jia Yan
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

An ontology is a explicit formal specification of a shared conceptualization. The application of Ontology in Component, Web Service, Ubiquitous Computing are now popular research topics. The Ontology technology is mainly applied in the semantic reform of the interface layer but not the implementation layer which makes the pre-process work be very large for the component’s consumer. In this paper, we propose a novel framework in which a calculating semanticability function has been added in the component. The calling request written in the nature language can be analyzed in this function. The ability value to solve the calling request is calculated in this function and the respective function to solve the calling request is selected. In other words, the automatic discovery, match and selection for the component and the relative function is realized in the component implement layer which greatly deduces the pre-process work for consumer. Moreover, an general calling function named uniExecute (string call_function_name, string para_str) is added in the traditional component where the parameter cal_function_name is the selected function in the traditional component. This method is high performance. Therefore, the low performance problem of executing function based on the IDispatch interface is been resolved. These approaches are applied in the application software operation evaluation system which demonstrates the effectiveness and efficiency of this approach.
A kernel approach to comparing distributions
Authors: Arthur Gretton, Karsten M. Borgwardt, Malte Rasch, Bernhard Scholköpf, Alexander J. Smola
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a Reproducing Kernel Hilbert Space. We apply this technique to construct a two-sample test, which is used for determining whether two sets of observations arise from the same distribution. We use this test in attribute matching for databases using the Hungarian marriage method, where it performs strongly. We also demonstrate excellent performance when comparing distributions over graphs, for which no alternative tests currently exist.