Edit distance

About: Edit distance is a research topic. Over the lifetime, 2887 publications have been published within this topic receiving 71491 citations.

EED: Extended Edit Distance Measure for Machine Translation

Abstract: Over the years a number of machine translation metrics have been developed in order to evaluate the accuracy and quality of machine-generated translations. Metrics such as BLEU and TER have been used for decades. However, with the rapid progress of machine translation systems, the need for better metrics is growing. This paper proposes an extension of the edit distance, which achieves better human correlation, whilst remaining fast, flexible and easy to understand.

SPEDE: Probabilistic Edit Distance Metrics for MT Evaluation

Abstract: This paper describes Stanford University's submission to the Shared Evaluation Task of WMT 2012. Our proposed metric (SPEDE) computes probabilistic edit distance as predictions of translation quality. We learn weighted edit distance in a probabilistic finite state machine (pFSM) model, where state transitions correspond to edit operations. While standard edit distance models cannot capture long-distance word swapping or cross alignments, we rectify these shortcomings using a novel pushdown automaton extension of the pFSM model. Our models are trained in a regression framework, and can easily incorporate a rich set of linguistic features. Evaluated on two different prediction tasks across a diverse set of datasets, our methods achieve state-of-the-art correlation with human judgments.

A tool for classifying office documents

Abstract: The authors present the design of a tool for classifying office documents. They represent a document's layout structure using an ordered labeled tree, called the layout structure tree (L-S-tree), based on a nested segmentation procedure. The tool uses a sample-based approach for learning, where concepts are learned by retaining samples and new documents are classified by matching their L-S-trees with samples. The matching process involves both computing the edit distance between two trees using a previously developed pattern matching toolkit, and calculating the degree of conceptual closeness between the documents and samples. The experimental results show that the tool is capable of classifying various types of office documents, even with very few samples in the sample base.

A Pattern‐Based Approach for Matching Nodes in Heterogeneous Urban Road Networks

Abstract: This article presents an approach to hierarchical matching of nodes in heterogeneous road networks inthe same urban area. Heterogeneous road networks not only exist at different levels of detail (LoD), butalso have different coordinate systems, leading to difficulties in matching and integrating them. To over-come these difficulties, a pattern-based method was implemented. Based on the authors’ previous work ondetecting patterns of divided highways, complex road junctions, and strokes to eliminate the LoD effectof road networks, the proposed method extracts the local networks around each node in a road networkand uses them as the matching units for the nodes. Second, the degree of shape similarity between thematching units is measured using a Minimum Road Edit Distance based on a transformation. Finally, theproposed method hierarchically matches the nodes in a road network using the Minimum Road Edit Dis-tance and eliminates false matching nodes using M-estimators. An experiment involving matching hetero-geneous road networks with different LoDs and coordinate systems was carried out to verify the validityof the proposed method. The method achieves good and effective matching regardless of differences inLoDs and road-network coordinate systems.

Finding Approximate Covers of Strings

Abstract: Repetitive strings have been studied in such diverse fields as molecular biology data compression etc. Some important regularities that have been studied are perods, covers seeds and squares. A natural extension of the repetition problems is to allow errors. Among the four notions above aproximate squares and approximate periodes have been studied. In this paper, we introduce the notion of approximate covers which is an approximate version of covers. Given two strings P(｜P｜=m) and T(｜T｜=n) we propose and algorithm with finds the minimum distance t such that P is a t-approximate cover of T. The algorithm take O(m,n) time for the edit distance and time of finding a string which is an approximate cover of T is minimum distance is NP-complete.