5803228
Vertex covering by paths on trees with its applications in machine translation
Given a tree and a set of paths in the tree, the problem of finding a minimum number of paths from the given path set to cover all the vertices in the tree is investigated in the paper. To distinguish from the classical path cover problem, such an optimization problem is referred to as vertex covering by paths. The problem and its edge variant, edge covering by paths, find applications in machine translation. Complexity and algorithmic results are presented for the problem and its edge variant.
2615651
A Probability Model to Improve Word Alignment
Word alignment plays a crucial role in statistical machine translation. Word-aligned corpora have been found to be an excellent source of translation-related knowledge. We present a statistical model for computing the probability of an alignment given a sentence pair. This model allows easy integration of context-specific features. Our experiments show that this model can be an effective tool for improving an existing word alignment.
5467372
Organizing and Searching the World Wide Web of Facts - Step One: The One-Million Fact Extraction Challenge
Due to the inherent difficulty of processing noisy text, the potential of the Web as a decentralized repository of human knowledge remains largely untapped during Web search. The access to billions of binary relations among named entities would enable new search paradigms and alternative methods for presenting the search results. A first concrete step towards building large searchable repositories of factual knowledge is to derive such knowledge automatically at large scale from textual documents. Generalized contextual extraction patterns allow for fast iterative progression towards extracting one million facts of a given type (e.g., Person-BornIn-Year) from 100 million Web documents of arbitrary quality. The extraction starts from as few as 10 seed facts, requires no additional input knowledge or annotated text, and emphasizes scale and coverage by avoiding the use of syntactic parsers, named entity recognizers, gazetteers, and similar text processing tools and resources.
1196662
A Nearest-Neighbor Method for Resolving PP-Attachment Ambiguity
We present a nearest-neighbor algorithm for resolving prepositional phrase attachment ambiguities. Its performance is significantly higher than previous corpus-based methods for PP-attachment that do not rely on manually constructed knowledge bases. We will also show that the PP-attachment task provides a way to evaluate methods for computing distributional word similarities. Our experiments indicate that the cosine of pointwise mutual information vector is a significantly better similarity measure than several other commonly used similarity measures.
18207470
Supporting intercultural collaboration: an agent coordination workflow model
Workflow management has already been worldwide accepted due to its capability to make organizations model and control work processes effectively and efficiently in a distributed environment. Currently, most of the workflow management systems (WfMSs) are lack of a coordination mechanism across different organizations. We first propose an intercultural collaboration workflow process definition and then propose an agent coordination workflow model based on the consideration of cultural factors in intercultural collaboration work process modeling.
8110502
Data Management in RFID Applications
Nowadays, RFID applications have attracted a great deal of interest due to their increasing adoptions in supply chain management, logistics and security. They have posed many new challenges to existing underlying database technologies, such as the requirements of supporting big volume data, preserving data transition path and handling new types of queries. In this paper, we propose an efficient method to manage RFID data.We explore and take advantage of the containment relationships in the relational tables in order to support special queries in the RFID applications. The experimental evaluation conducted on an existing RDBMS demonstrates the efficiency of our method.
6409436
Word-for-Word Glossing with Contextually Similar Words
Many corpus-based machine translation systems require parallel corpora. In this paper, we present a word-for-word glossing algorithm that requires only a source language corpus. To gloss a word, we first identify its similar words that occurred in the same context in a large corpus. We then determine the gloss by maximizing the similarity between the set of contextually similar words and the different translations of the word in a bilingual thesaurus.
22202534
Subspace-based active user identification for a collision-free slotted ad hoc network
We propose a novel spreading code scheme, transmitter-receiver-based code, for wireless ad hoc networks. The design facilitates collision resolution using multiuser detection at each node, and is more bandwidth efficient than creating orthogonal channels in time or frequency. A subspace-based receiver structure is introduced, which identifies users of interest, or "active" users, with minimal prior information on the spreading code ensemble. A subspace-based blind multiuser detector can then be implemented to suppress multiaccess interference. The performance of the proposed active user identifier is studied by investigating its false alarm rate P/sub f/ and miss rate P/sub m/. Tradeoffs between P/sub f/ and P/sub m/ are discussed, and a graphical method to determine the threshold value d/sub th/ of the decision statistic used in discriminating between active and inactive channels is introduced.
1394805
Using Syntactic Dependency as Local Context to Resolve Word Sense Ambiguity
Most previous corpus-based algorithms disambiguate a word with a classifier trained from previous usages of the same word. Separate classifiers have to be trained for different words. We present an algorithm that uses the same knowledge sources to disambiguate different words. The algorithm does not require a sense-tagged corpus and exploits the fact that two different words are likely to have similar meanings if they occur in identical local contexts.