Alex Faaborg, Henry Lieberman

Users have high-level goals when they browse the Web or perform searches. However, the two primary user interfaces positioned between users and the Web, Web browsers and search engines, have very little interest in users' goals. Present-day Web browsers provide only a thin interface between users and the Web, and present-day search engines rely solely on keyword matching. This thesis leverages large knowledge bases of semantic information to provide users with a goal-oriented Web browsing experience. By understanding the meaning of Web pages and search queries, this thesis demonstrates how Web browsers and search engines can proactively suggest content and services to users that are both contextually relevant and personalized.

 

Andrew Wang, Alex Faaborg, Jose Espinosa, Henry Lieberman

When computers automatically generate video game environments, the result is often as simplistic as a randomly generated maze. Using the Open Mind Common Sense knowledge base, we are exploring ways to automatically generate virtual environments that are immersive and intelligently designed. By allowing video games to dynamically create their own environments, developers will be able to reduce the time they currently spend crafting environments by hand and focus on higher level design issues. More importantly, games that are capable of changing their own environments will feel less static, resulting in a more believable experience and an increased replay value.

Video: Dynamically Generating Video Game Environments

Waseem Daher, Jose Espinosa, Alex Faaborg, Henry Lieberman

Current speech recognition software relies on statistical techniques to determine which words a user has said. In this project we are attempting to leverage the semantic context of what the user has previously said to improve future predictions. We are using ConceptNet, a semantic network created from the Open Mind Common Sense knowledge base to disambiguate phonetically similar words and improve overall recognition accuracy.

Video: Speech Recognition

Alex Faaborg, Chris Tsai, Henry Lieberman

The goal of this project is to create an agent that predicts tasks users may be interested in adding to their to-do list, based on the context of appointments they are adding to their calendar. The agent uses Commonsense Reasoning to predict tasks that users are likely to add. For instance, if the user makes the calendar appointment “go fishing”, the agent may recommend the task “pack fishing equipment.” By automatically generating potential tasks, the agent will save user’s time, and will help them remember actions they may commonly forget.

Video: Anticipating User Tasks

Alex Faaborg, Chris Tsai, Henry Lieberman, Judith Donath

Cell phone contact lists represent a very large peer-to-peer network. We are creating a cell phone based application that allows users to perform real time searches on their local social network, against pieces of information that their contacts have provided about themselves. Our matchmaking agent uses Open Mind Common Sense to understand users’ goals, and logically expand on their queries.

Video: Searching Social Networks

Jose Espinosa, Alex Faaborg, Henry Lieberman

When traveling in foreign countries, people often rely on traditional phrase books for language translation. However, these phrase books only work in a limited number of common situations, and even common situations will often deviate from the predefined script the phrase book relies on. Using a vast knowledge base of commonsense facts and relationships, GloBuddy 2 is able to expand on the user’s translation request and provide words and phrases related to the user’s situation.

Video: A Tourist's Phrase Book