Automated Program Description

The Programmer's apprentice (PA) is an automated program development tool. The PA depends upon a library of common algorithms (cliches) as the source of its knowledge about programming. The PA uses these cliches to understand how a program is implemented. This knowledge may also be used to explain to a user of the PA how the program is implemented. The problem with any explanation or description is knowing how much information to present, and how much information to hide. A set of simple heuristics for doing this can be used with the cliche representation of a program to produce reasonable descriptions of parts of programs. The system described combines "canned" phrases corresponding to cliche parts to form explanations. The process is fast and appears to be easily extensible to future versions of the PA and other domains.MIT Artificial Intelligence Laborator

Field crossings : hybridizing the urban park

Thesis (M.Arch.)--Massachusetts Institute of Technology, Dept. of Architecture, 2003.Includes bibliographical references (p. 102-103).The growth and identity of urban open space is a vital issue facing our cities today. The development and revitalization of old industrial centers in the United States has prompted urban transformations in usage, densification and demographics. These shifting neighborhoods call for a reconsideration of the makeup and syntax of their associated green spaces. The design of this urban landscape is not currently positioned to take advantage of limited spatial opportunities while meeting increasingly diverse programmatic needs. Traditional park typologies must respond to contemporary forces, varying leisure practices and allow for new interactions with an evolving city. This thesis posits a new model for parks and their architecture within changing urban neighborhoods. It explores how parks can accommodate these transformations through the topics of imbedded infrastructure, flexibility, prototyping and merging public and private usage. It seeks to create more humane and vital open spaces by adding functional and diversified occupations that respond to specific contextual requirements. This thesis looks to understand how both the landscape and its built architecture can work together to become a more viable model for the next century.Scott Marshall Cyphers.M.Arch

A Vector Space Approach for Aspect Based Sentiment Analysis

Abstract Vector representations for language has been shown to be useful in a number of Natural Language Processing tasks. In this paper, we aim to investigate the effectiveness of word vector representations for the problem of Aspect Based Sentiment Analysis. In particular, we target three sub-tasks namely aspect term extraction, aspect category detection, and aspect sentiment prediction. We investigate the effectiveness of vector representations over different text data and evaluate the quality of domain-dependent vectors. We utilize vector representations to compute various vectorbased features and conduct extensive experiments to demonstrate their effectiveness. Using simple vector based features, we achieve F1 scores of 79.91% for aspect term extraction, 86.75% for category detection, and the accuracy 72.39% for aspect sentiment prediction