Brent Hecht

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Brent Hecht is an author.

Publications

Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Explanatory semantic relatedness and explicit spatialization for exploratory search Cartography
Exploratory search
Geography
Giscience
Semantic relatedness
Spatialization
Text mining
Wikipedia
SIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval English 2012 Exploratory search, in which a user investigates complex concepts, is cumbersome with today's search engines. We present a new exploratory search approach that generates interactive visualizations of query concepts using thematic cartography (e.g. choropleth maps, heat maps). We show how the approach can be applied broadly across both geographic and non-geographic contexts through explicit spatialization, a novel method that leverages any figure or diagram - from a periodic table, to a parliamentary seating chart, to a world map - as a spatial search environment. We enable this capability by introducing explanatory semantic relatedness measures. These measures extend frequently-used semantic relatedness measures to not only estimate the degree of relatedness between two concepts, but also generate human-readable explanations for their estimates by mining Wikipedia's text, hyperlinks, and category structure. We implement our approach in a system called Atlasify, evaluate its key components, and present several use cases. 0 0
Omnipedia: Bridging the Wikipedia Language Gap Wikipedia
Hyperlingual
Language barrier
User generated content
Text mining
International Conference on Human Factors in Computing Systems English 2012 We present Omnipedia, a system that allows Wikipedia readers to gain insight from up to 25 language editions ofWikipedia simultaneously. Omnipedia highlights the similarities and differences that exist among Wikipedia language editions, and makes salient information that is unique to each language as well as that which is shared more widely. We detail solutions to numerous front-end and algorithmic challenges inherent to providing users with a multilingual Wikipedia experience. These include visualizing content in a language-neutral way and aligning data in the face of diverse information organization strategies. We present a study of Omnipedia that characterizes how people interact with information using a multilingual lens. We found that users actively sought information exclusive to unfamiliar language editions and strategically compared how language editions defined concepts. Finally, we briefly discuss how Omnipedia generalizes to other domains facing language barriers. 0 0
Omnipedia: Bridging the Wikipedia language gap Hyperlingual
Language barrier
Text mining
User generated content
Wikipedia
Conference on Human Factors in Computing Systems - Proceedings English 2012 We present Omnipedia, a system that allows Wikipedia readers to gain insight from up to 25 language editions of Wikipedia simultaneously. Omnipedia highlights the similarities and differences that exist among Wikipedia language editions, and makes salient information that is unique to each language as well as that which is shared more widely. We detail solutions to numerous front-end and algorithmic challenges inherent to providing users with a multilingual Wikipedia experience. These include visualizing content in a language-neutral way and aligning data in the face of diverse information organization strategies. We present a study of Omnipedia that characterizes how people interact with information using a multilingual lens. We found that users actively sought information exclusive to unfamiliar language editions and strategically compared how language editions defined concepts. Finally, we briefly discuss how Omnipedia generalizes to other domains facing language barriers. Copyright 2012 ACM. 0 0
The Tower of Babel Meets Web 2.0: User-Generated Content and Its Applications in a Multilingual Context International Conference on Human Factors in Computing Systems English 2010 This study explores language's fragmenting effect on user-generated content by examining the diversity of knowledge representations across 25 different Wikipedia language editions. This diversity is measured at two levels: the concepts that are included in each edition and the ways in which these concepts are described. We demonstrate that the diversity present is greater than has been presumed in the literature and has a significant influence on applications that use Wikipedia as a source of world knowledge. We close by explicating how knowledge diversity can be beneficially leveraged to create "culturally-aware applications" and "hyperlingual applications". 0 2
The tower of Babel meets web 2.0: User-generated content and its applications in a multilingual context Explicit semantic analysis
Hyperlingual
Knowledge diversity
Language
Semantic relatedness
Wikipedia
Conference on Human Factors in Computing Systems - Proceedings English 2010 This study explores language's fragmenting effect on user-generated content by examining the diversity of knowledge representations across 25 different Wikipedia language editions. This diversity is measured at two levels: the concepts that are included in each edition and the ways in which these concepts are described. We demonstrate that the diversity present is greater than has been presumed in the literature and has a significant influence on applications that use Wikipedia as a source of world knowledge. We close by explicating how knowledge diversity can be beneficially leveraged to create "culturally- aware applications" and "hyperlingual applications". 0 2
Measuring Self-Focus Bias in Community-Maintained Knowledge Repositories International Conference on Communities and Technologies English 2009 Self-focus is a novel way of understanding a type of bias in community-maintained Web 2.0 graph structures. It goes beyond previous measures of topical coverage bias by encapsulating both node- and edge-hosted biases in a single holistic measure of an entire community-maintained graph. We outline two methods to quantify self-focus, one of which is very computationally inexpensive, and present empirical evidence for the existence of self-focus using a "hyperlingual" approach that examines 15 different language editions of Wikipedia. We suggest applications of our methods and discuss the risks of ignoring self-focus bias in technological applications. 0 0
Terabytes of tobler: Evaluating the first law in a massive, domain-neutral representation of world knowledge First Law of Geography
Spatial Autocorrelation
Spatial Dependence
Tobler's Law
Wikipedia
Lecture Notes in Computer Science English 2009 The First Law of Geography states, "everything is related to everything else, but near things are more related than distant things." Despite the fact that it is to a large degree what makes "spatial special," the law has never been empirically evaluated on a large, domain-neutral representation of world knowledge. We address the gap in the literature about this critical idea by statistically examining the multitude of entities and relations between entities present across 22 different language editions of Wikipedia. We find that, at least according to the myriad authors of Wikipedia, the First Law is true to an overwhelming extent regardless of language-defined cultural domain. 0 0
GeoSR: Geographically explore semantic relations in world knowledge Geographic reference system
GeoSR
Natural Language Processing
Semantic relatedness
Wikipedia
Lecture Notes in Geoinformation and Cartography English 2008 Methods to determine the semantic relatedness (SR) value between two lexically expressed entities abound in the field of natural language processing (NLP). The goal of such efforts is to identify a single measure that summarizes the number and strength of the relationships between the two entities. In this paper, we present GeoSR, the first adaptation of SR methods to the context of geographic data exploration. By combining the first use of a knowledge repository structure that is replete with non-classical relations, a new means of explaining those relations to users, and the novel application of SR measures to a geographic reference system, GeoSR allows users to geographically navigate and investigate the world knowledge encoded in Wikipedia. There are numerous visualization and interaction paradigms possible with GeoSR; we present one implementation as a proof-of-concept and discuss others. Although, Wikipedia is used as the knowledge repository for our implementation, GeoSR will also work with any knowledge repository having a similar set of properties. 0 0
Geographically Explore Semantic Relations in World Knowledge English 2008 0 0
Improving interaction with virtual globes through spatial thinking: Helping users ask "Why?" Artificial intelligence
Multi-touch interaction
Semantic relatedness
Spatial thinking
Virtual globes
Wall-size interfaces
Wikipedia
International Conference on Intelligent User Interfaces, Proceedings IUI English 2008 Virtual globes have progressed from little-known technology to broadly popular software in a mere few years. We investigated this phenomenon through a survey and discovered that, while virtual globes are en vogue, their use is restricted to a small set of tasks so simple that they do not involve any spatial thinking. Spatial thinking requires that users ask "what is where" and "why"; the most common virtual globe tasks only include the "what". Based on the results of this survey, we have developed a multi-touch virtual globe derived from an adapted virtual globe paradigm designed to widen the potential uses of the technology by helping its users to inquire about both the "what is where" and "why" of spatial distribution. We do not seek to provide users with full GIS (geographic information system) functionality, but rather we aim to facilitate the asking and answering of simple "why" questions about general topics that appeal to a wide virtual globe user base. Copyright 2008 ACM. 0 0
Generating Educational Tourism Narratives from Wikipedia Narrative theory
Data mining
Educational tourism
Association for the Advancement of Artificial Intelligence Fall Symposium on Intelligent Narrative Technologies (AAAI-INT) 2007 We present a narrative theory-based approach to data mining that generates cohesive stories from a Wikipedia corpus. This approach is based on a data mining-friendly view of narrative derived from narratology, and uses a prototype mining algorithm that implements this view. Our initial test case and focus is that of field-based educational tour narrative generation, for which we have successfully implemented a proof-of-concept system called Minotour. This system operates on a client-server model, in which the server mines a Wikipedia database dump to generate narratives between any two spatial features that have associated Wikipedia articles. The server then delivers those narratives to mobile device clients. 0 0
Generating educational tourism narratives from wikipedia AAAI Fall Symposium - Technical Report English 2007 We present a narrative theory-based approach to data mining that generates cohesive stories from a Wikipedia corpus. This approach is based on a data mining-friendly view of narrative derived from narratology, and uses a prototype mining algorithm that implements this view. Our initial test case and focus is that of field-based educational tour narrative generation, for which we have successfully implemented a proof-of-concept system called Minotour. This system operates on a client-server model, in which the server mines a Wikipedia database dump to generate narratives between any two spatial features that have associated Wikipedia articles. The server then delivers those narratives to mobile device clients. 0 0
WikEye - Using Magic Lenses to Explore Georeferenced Wikipedia Content. Wikipedia data-mining
Magic lens
Augmented reality
Markerless tracking
3rd International Workshop on Pervasive Mobile Interaction Devices (PERMID) in Conjuncation with Pervasive Computing 2007 0 0