5927994
A New Approach to Modeling Personal Office Documents
Abstract This paper proposes a new approach to modeling documents in a personal office environment. The proposed document model (called the D _model) combines the relational and object-oriented paradigms and adopts a very natural view for describing the office documents. Documents are grouped into classes. Each class is characterized by a frame template, which describes the type for the class of documents. A frame template is instantiated by providing it with values to form a frame instance, representing a synopsis of a particular document associated with the template. Based on the nature of their contents, different frame instances can be grouped into a folder. Thus, a folder is a set of frame instances which may or may not be associated with the same template. The D _model describes documents using dual hierarchies: a document type hierarchy, depicting the structural organization of the documents, and a folder organization, representing the user's logical file structure. The document type hierarchy exploits structural commonalities between frame templates. Such a hierarchy helps to classify various documents. The folder organization mimics the user's real-world document filing system and provides the user with an intuitively clear view of his/her file structure. Such a view facilitates document retrieval and filing activities. We also present an algebra (called the D _algebra) for manipulating frame instances contained in folders. In contrast to existing algebraic languages, the D _algebra provides operators for manipulating heterogeneous sets (i.e. sets with elements of different types). The proposed document model and algebraic language have been implemented as part of TEXPROS, a personal document processing system currently running in our laboratory.
2286283
Query result ranking over e-commerce web databases
To deal with the problem of too many results returned from an E-commerce Web database in response to a user query, this paper proposes a novel approach to rank the query results. Based on the user query, we speculate how much the user cares about each attribute and assign a corresponding weight to it. Then, for each tuple in the query result, each attribute value is assigned a score according to its "desirableness" to the user. These attribute value scores are combined according to the attribute weights to get a final ranking score for each tuple. Tuples with the top ranking scores are presented to the user first. Our ranking method is domain independent and requires no user feedback. Experimental results demonstrate that this ranking method can effectively capture a user's preferences.
12680145
Finding Patterns in Three-Dimensional Graphs: Algorithms and Applications to Scientific Data Mining
Presents a method for finding patterns in 3D graphs. Each node in a graph is an undecomposable or atomic unit and has a label. Edges are links between the atomic units. Patterns are rigid substructures that may occur in a graph after allowing for an arbitrary number of whole-structure rotations and translations as well as a small number (specified by the user) of edit operations in the patterns or in the graph. (When a pattern appears in a graph only after the graph has been modified, we call that appearance "approximate occurrence.") The edit operations include relabeling a node, deleting a node and inserting a node. The proposed method is based on the geometric hashing technique, which hashes node-triplets of the graphs into a 3D table and compresses the label-triplets in the table. To demonstrate the utility of our algorithms, we discuss two applications of them in scientific data mining. First, we apply the method to locating frequently occurring motifs in two families of proteins pertaining to RNA-directed DNA polymerase and thymidylate synthase and use the motifs to classify the proteins. Then, we apply the method to clustering chemical compounds pertaining to aromatic compounds, bicyclicalkanes and photosynthesis. Experimental results indicate the good performance of our algorithms and high recall and precision rates for both classification and clustering.
14900181
Unordered tree mining with applications to phylogeny
Frequent structure mining (FSM) aims to discover and extract patterns frequently occurring in structural data, such as trees and graphs. FSM finds many applications in bioinformatics, XML processing, Web log analysis, and so on. We present a new FSM technique for finding patterns in rooted unordered labeled trees. The patterns of interest are cousin pairs in these trees. A cousin pair is a pair of nodes sharing the same parent, the same grandparent, or the same great-grandparent, etc. Given a tree T, our algorithm finds all interesting cousin pairs of T in O(|T|/sup 2/) time where |T| is the number of nodes in T. Experimental results on synthetic data and phylogenies show the scalability and effectiveness of the proposed technique. To demonstrate the usefulness of our approach, we discuss its applications to locating co-occurring patterns in multiple evolutionary trees, evaluating the consensus of equally parsimonious trees, and finding kernel trees of groups of phylogenies. We also describe extensions of our algorithms for undirected acyclic graphs (or free trees).
236203
New Techniques for DNA Sequence Classification
DNA sequence classification is the activity of determining whether or not an unlabeled sequence S belongs to an existing class C. This paper proposes two new techniques for DNA sequence classification. The first technique works by comparing the unlabeled sequence S with a group of active motifs discovered from the elements of C and by distinction with elements outside of C. The second technique generates and matches gapped fingerprints of S with elements of C. Experimental results obtained by running these algorithms on long and well conserved Alu sequences demonstrate the good performance of the presented methods compared with FASTA. When applied to less conserved and relatively short functional sites such as splice-junctions, a variation of the second technique combining fingerprinting with consensus sequence analysis gives better results than the current classifiers employing text compression and machine learning algorithms.
11616193
Automatic Hierarchical Classification of Structured Deep Web Databases
We present a method that automatically classifies structured deep Web databases according to a pre-defined topic hierarchy. We assume that there are some manually classified databases, i.e., training databases, in every node of the topic hierarchy. Each training database is probed using queries constructed from the node titles of the topic hierarchy and the query result counts reported by the database are used to represent the content of the database. Hence, when adding a new database it can be probed by the same set of queries and classified to a node whose training databases are most similar to the new one. Specifically, a support vector machine classifier is trained on each internal node of the topic hierarchy with these training databases and the new database can be classified into the hierarchy top-down level by level. A feature extension method is proposed to create discriminant features. Experiments run on real structured Web databases collected from the Internet show that this classification method is quite accurate.
6804856
Processing rate optimization by sequential system floorplanning
The performance of a sequential system is usually measured by its frequency. However, with the appearance of global interconnects that require multiple clock periods to communicate the throughput is usually traded-off for higher frequency (for example, through wire pipelining or latency insensitive design). Therefore, we propose to use the processing rate, defined as the amount of processed inputs per unit time, as the performance measure. We show that the minimal ratio of the flip-flop number over the delay on any cycle is an upper bound of the processing rate. Since the processing rate of a sequential system is mainly decided by its floorplan when interconnect delays are dominant, the problem of floorplanning for processing rate optimization is formulated and solved. We optimize the processing rate bound directly in a floorplanner by applying Howard's algorithm incrementally. Experimental results confirm the effectiveness of our approach
14843520
Deriving knowledge from figures for digital libraries
Figures in digital documents contain important information. Current digital libraries do not summarize and index information available within figures for document retrieval. We present our system on automatic categorization of figures and extraction of data from 2-D plots. A machine-learning based method is used to categorize figures into a set of predefined types based on image features. An automated algorithm is designed to extract data values from solid line curves in 2-D plots. The semantic type of figures and extracted data values from 2-D plots can be integrated with textual information within documents to provide more effective document retrieval services for digital library users. Experimental evaluation has demonstrated that our system can produce results suitable for real-world use.
35219345
Integrated architectural modeling and analysis for high-assurance command and control system design
A real-time architectural specification (RAS) approach and its application to command and control (C2) systems are presented. The objective is to establish a formal foundation that will enable us to integrate existing rich but fragmented formal techniques for system specification and verification into practical and scaleable formal engineering methods to support the design and development of highly reliable real-time distributed systems. The contribution of RAS is twofold; first, it provides a formal system that integrates the system's timing requirements and the propagation of the requirements into the process of architectural modeling and design and provides a systematic way to enforce that the requirements are met in every step of the design process. Second, it offers an incremental and more scalable approach for design modeling. These two features together make RAS a suitable model for the design of C2 systems. Based on these features, we further present an incremental method for verifying timing properties of a RAS model that helps to reduce the complexity of analysis both at a given design level or across different design levels.
2455178
Voice conversion using duration-embedded bi-HMMs for expressive speech synthesis
This paper presents an expressive voice conversion model (DeBi-HMM) as the post processing of a text-to-speech (TTS) system for expressive speech synthesis. DeBi-HMM is named for its duration-embedded characteristic of the two HMMs for modeling the source and target speech signals, respectively. Joint estimation of source and target HMMs is exploited for spectrum conversion from neutral to expressive speech. Gamma distribution is embedded as the duration model for each state in source and target HMMs. The expressive style-dependent decision trees achieve prosodic conversion. The STRAIGHT algorithm is adopted for the analysis and synthesis process. A set of small-sized speech databases for each expressive style is designed and collected to train the DeBi-HMM voice conversion models. Several experiments with statistical hypothesis testing are conducted to evaluate the quality of synthetic speech as perceived by human subjects. Compared with previous voice conversion methods, the proposed method exhibits encouraging potential in expressive speech synthesis
15313247
Performance of a MAC protocol for WDM networks with on-line scheduling
This paper investigates the performance of media access protocols based on on-line scheduling for an optically connected star-coupled system with wavelength division multiple access channels. Hybrid access protocols combining reservation and pre-allocation of receiver channels have been previously proposed. Transmission consisted of a reservation phase followed by a data phase. Each node was allowed to place a reservation for one WDM channel. This protocol is extended in this paper by allowing reservations on multiple channels and using simple on-line scheduling algorithms. Existing scheduling algorithms (all are off-line) for similar reservation problems tend to have high implementation and computational complexity. We require that scheduling algorithms be real-time and amenable to hardware implementation. The performance of the extended protocol incorporating two simple on-line scheduling algorithms is presented in this paper. We show that the slight increased computational overhead with scheduling is justified by reduced packet latency and higher utilization, especially for client-server traffic.