6727358
Segmenting meetings into agenda items by extracting implicit supervision from human note-taking
Splitting a meeting into segments such that each segment contains discussions on exactly one agenda item is useful for tasks such as retrieval and summarization of agenda item discussions. However, accurate topic segmentation of meetings is a difficult task. In this paper, we investigate the idea of acquiring implicit supervision from human meeting participants to solve the segmentation problem. Specifically we have implemented and tested a note taking interface that gives value to users by helping them organize and retrieve their notes easily, but that also extracts a segmentation of the meeting based on note taking behavior. We show that the segmentation so obtained achieves a Pk value of 0.212 which improves upon an unsupervised baseline by 45% relative, and compares favorably with a current state-of-the-art algorithm. Most importantly, we achieve this performance without any features or algorithms in the classic sense.
40585807
Using Measures of Semantic Relatedness for Word Sense Disambiguation
This paper generalizes the Adapted Lesk Algorithm of Banerjee and Pedersen (2002) to a method of word sense disambiguation based on semantic relatedness. This is possible since Lesk's original algorithm (1986) is based on gloss overlaps which can be viewed as a measure of semantic relatedness. We evaluate a variety of measures of semantic relatedness when applied to word sense disambiguation by carrying out experiments using the English lexical sample data of SENSEVAL-2. We find that the gloss overlaps of Adapted Lesk and the semantic distance measure of Jiang and Conrath (1997) result in the highest accuracy.
56684730
Extended Gloss Overlaps as a Measure of Semantic Relatedness
This paper presents a new measure of semantic relatedness between concepts that is based on the number of shared words (overlaps) in their definitions (glosses). This measure is unique in that it extends the glosses of the concepts under consideration to include the glosses of other concepts to which they are related according to a given concept hierarchy. We show that this new measure reasonably correlates to human judgments. We introduce a new method of word sense disambiguation based on extended gloss overlaps, and demonstrate that it fares well on the SENSEVAL-2 lexical sample data.
2969941
SmartNotes: Implicit Labeling of Meeting Data through User Note-Taking and Browsing
We have implemented SmartNotes, a system that automatically acquires labeled meeting data as users take notes during meetings and browse the notes afterwards. Such data can enable meeting understanding components such as topic and action item detectors to automatically improve their performance over a sequence of meetings. The SmartNotes system consists of a laptop based note taking application, and a web based note retrieval system. We shall demonstrate the functionalities of this system, and will also demonstrate the labeled data obtained during typical meetings and browsing sessions.
11158
SenseRelate: : TargetWord-A Generalized Framework for Word Sense Disambiguation
Many words in natural language have different meanings when used in different contexts. Sense Relate: Target Word is a Perl package that disambiguates a target word in context by finding the sense that is most related to its neighbors according to a WordNet: Similarity measure of relatedness.
206616812
The Design, Implementation, and Use of the Ngram Statistics Package
The Ngram Statistics Package (NSP) is a flexible and easy-to-use software tool that supports the identification and analysis of Ngrams, sequences of N tokens in online text. We have designed and implemented NSP to be easy to customize to particular problems and yet remain general enough to serve a broad range of needs. This paper provides an introduction to NSP while raising some general issues in Ngram analysis, and summarizes several applications where NSP has been successfully employed. NSP is written in Perl and is freely available under the GNU Public License.
711206
Performance optimizations for wireless wide-area networks: comparative study and experimental evaluation
We present a comparative performance study of a wide selection of optimization techniques to enhance application performance in the context of wide-area wireless networks (WWANs). Unlike in traditional wired and wireless IP-based networks, applications running over WWAN cellular environments are significantly affected by the vagaries of the cellular wireless medium. Prior research has proposed and analyzed optimizations at individual layers of the protocol stack. In contrast, we introduce the first detailed experiment-based evaluation and comparison of all such optimization techniques in a commercial WWAN testbed. This paper, therefore, summarizes our experience in implementing and deploying an infrastructure to improve WWAN performance.The goals of this paper are: (1) to perform an accurate benchmark of application performance over such commercially deployed WWAN environments, (2) to implement and characterize the impact of various optimization techniques across different layers of the protocol stack, and (3) to quantify their interdependencies in realistic scenarios. Additionally, we also discuss measurement pitfalls that we experienced and provide guidelines that may be useful for future experimentation in WWAN environments.
16981937
Network traffic characterization of distributed database applications
The authors' efforts in characterizing the traffic of distributed database systems are described. This is an important class of applications considering that database or transaction processing systems form the core of several key commercial applications. Specific traffic source models for this application class have not been developed which is imperative for their successful deployment in emerging networks. The main contribution of the paper is to present the relationship between a distributed database application scenario and the corresponding network traffic characteristics, thus providing guidelines to these applications to compute their traffic descriptors accurately.
17891154
A Credit-Based Active Queue Management (AQM) Mechanism to Achieve Fairness in the Internet
Router-based algorithms to address the TCP-friendliness problem have focused on providing fairness to TCP connections by penalizing UDP unresponsive flows. As a result, current schemes have overlooked their effect on streaming applications. In addition, current schemes have not been widely implemented in practice because of their high complexity and their inability to provide fairness when multiple unresponsive flows, packets of different sizes, and bursty traffic are present. All these aspects and scenarios, commonly found in practice, are rarely addressed in the literature. In this paper, we present Achieving Fairness using a Credit-based mechanism or AFC, a simple Fair Active Queue Management (FAQM) mechanism that aims to solve the unfairness problems generated under these realistic conditions. Simulation results show that AFC provides smoother transfer rates for unresponsive flows transmitting real-time traffic, handles multiple heavy unresponsive flows better, improves the fairness among TCP connections with different round-trip delays, and achieves good fairness even under bursty traffic and packets of different sizes.
30095382
Performance Analysis of Generalized Selective Packet Discarding Schemes
Selective packet discarding schemes have been mostly developed and analyzed in the context of ATM networks. However, similar schemes could be applied to non-ATM or more general networks. The analysis of selective packet discarding schemes in a general packet switching environment has been limited to the basic dropping schemes, i.e., Partial Packet Discard (PPD) and Early Packet Discard (EPD), and for only the single traffic source case. In this paper, we extend the mathematical analysis of PPD and EPD for multiple sources and include simulation results to verify the analytical results. Finally, to place the performance of the generalized EPD and PPD in the context of other packet dropping schemes, we also provide simulation results of the Drop from Front (DfF), and preemptive Partial Packet Discard (pPPD) schemes.
16477654
Efficient peer location on the Internet
We consider the problem of locating nearby application peers over the Internet. We define a new peer-location scheme (called Tiers), that scales to large application peer groups. Tiers creates a hierarchy of peers, and provides an efficient and scalable solution to the peer-location problem. Tiers can be implemented entirely in the application-layer and does not require the deployment of either any additional measurement services, or well-known reference points in the network.We have evaluated the performance of Tiers through detailed experiments. Our results show that Tiers is able to locate the nearest peers quickly (≪ 1 s) and accurately on wide-area Internet-like topologies. We have also compared the performance of Tiers with two other schemes, Beaconing and Distributed Binning, both of which are known to have good performance. Both these techniques are reference-points based schemes and are efficient for overlays with a small number of peers (e.g. ≤32). Our results show that Tiers significantly outperforms both these schemes. Tiers is particularly efficient for large overlay networks, has an order of magnitude lower control overhead for overlays with 512 peers and still achieves greater accuracy in locating the nearest peers.