3,473 research outputs found
TimeMachine: Timeline Generation for Knowledge-Base Entities
We present a method called TIMEMACHINE to generate a timeline of events and
relations for entities in a knowledge base. For example for an actor, such a
timeline should show the most important professional and personal milestones
and relationships such as works, awards, collaborations, and family
relationships. We develop three orthogonal timeline quality criteria that an
ideal timeline should satisfy: (1) it shows events that are relevant to the
entity; (2) it shows events that are temporally diverse, so they distribute
along the time axis, avoiding visual crowding and allowing for easy user
interaction, such as zooming in and out; and (3) it shows events that are
content diverse, so they contain many different types of events (e.g., for an
actor, it should show movies and marriages and awards, not just movies). We
present an algorithm to generate such timelines for a given time period and
screen size, based on submodular optimization and web-co-occurrence statistics
with provable performance guarantees. A series of user studies using Mechanical
Turk shows that all three quality criteria are crucial to produce quality
timelines and that our algorithm significantly outperforms various baseline and
state-of-the-art methods.Comment: To appear at ACM SIGKDD KDD'15. 12pp, 7 fig. With appendix. Demo and
other info available at http://cs.stanford.edu/~althoff/timemachine
Event-based Access to Historical Italian War Memoirs
The progressive digitization of historical archives provides new, often
domain specific, textual resources that report on facts and events which have
happened in the past; among these, memoirs are a very common type of primary
source. In this paper, we present an approach for extracting information from
Italian historical war memoirs and turning it into structured knowledge. This
is based on the semantic notions of events, participants and roles. We evaluate
quantitatively each of the key-steps of our approach and provide a graph-based
representation of the extracted knowledge, which allows to move between a Close
and a Distant Reading of the collection.Comment: 23 pages, 6 figure
Harvesting Context and Mining Emotions Related to Olfactory Cultural Heritage
UIDB/00657/2020
UIDP/00657/2020This paper presents an Artificial Intelligence approach to mining context and emotions related to olfactory cultural heritage narratives, particularly to fairy tales. We provide an overview of the role of smell and emotions in literature, as well as highlight the importance of olfactory experience and emotions from psychology and linguistic perspectives. We introduce a methodology for extracting smells and emotions from text, as well as demonstrate the context-based visualizations related to smells and emotions implemented in a novel smell tracker tool. The evaluation is performed using a collection of fairy tales from Grimm and Andersen. We find out that fairy tales often connect smell with the emotional charge of situations. The experimental results show that we can detect smells and emotions in fairy tales with an F1 score of 91.62 and 79.2, respectively.publishersversionpublishe
"Lei of Green" Revisiting the "Dream"
The purpose of this project is to design walkable solutions for Honolulu, by overcoming gaps and separations caused by various transportation barriers that create dis-connectivity, with parks, beaches, landmarks, schools and communities. The research focuses on âbuilding upon the shoulders of those who preceded usâ. Previous project visions will be used as the foundation to inspire new ideas and designs to solve Honoluluâs âwalkabilityâ issues. The original âLei of Greenâ design proposal created by the late Mr. Tom Papandrew, proposed design solutions and guidelines that promote walkability, recreation, safety and connectivity within an urban city. This doctorate project will be using Mr. Papandrewâs idea and other past examples of work, related to the âLei of Greenâ, to create a stronger foundation of research, to support the design segment of this doctorate project. This study is the outcome of five main areas of research: 1) studies on a previous bike proposal for Oâahu; 2) LEED â Neighborhood Development Criteria; 3) âThe Image of the Cityâ book written by Kevin Lynch; 4) Defining and finding the design criteria and benefits of both, Walkable Communities and Greenways; and 5) an interpretation of select case studies that embody both walkability and greenways. The result of all studies will shape the design benchmarks that will comprise the foundation for the final design proposal, of a sustainable walkable greenway system in Honolulu. This greenway system will be used to connect parks, beaches, landmarks, schools and communities to each other, to promote alternative transportation means, safety, additional tourist attractions, preserve existing green spaces and to instill Hawaiâi âsense of placeâ and cultural values that make Hawaiâi a unique destination. This research will provide a basic understanding of a walkable greenway design to eliminate gaps and separations within a community that can be used to create a walkable city for Honolulu
Is there a Correlation Between Wikidata Revisions and Trending Hashtags on Twitter?
Twitter is a microblogging application used by its members to interact and stay socially connected by sharing instant messages called tweets that are up to 280 characters long. Within these tweets, users can add hashtags to relate the message to a topic that is shared among users. Wikidata is a central knowledge base of information relying on its members and machines bots to keeping its content up to date. The data is stored in a highly structured format with the added SPARQL protocol and RDF Query Language (SPARQL) endpoint to allow users to query its knowledge base
Emergent Capabilities for Collaborative Teams in the Evolving Web Environment
This paper reports on our investigation of the latest advances for the Social Web, Web 2.0 and the Linked Data Web. These advances are discussed in terms of the latest capabilities that are available (or being made available) on the Web at the time of writing this paper. Such capabilities can be of significant benefit to teams, especially those comprised of multinational, geographically-dispersed team members. The specific context of coalition members in a rapidly formed diverse military context such as disaster relief or humanitarian aid is considered, where close working between non-government organisations and non-military teams will help to achieve results as quickly and efficiently as possible. The heterogeneity one finds in such teams, coupled with a lack of dedicated private network infrastructure, poses a number of challenges for collaboration, and the current paper represents an attempt to assess whether nascent Web-based capabilities can support such teams in terms of both their collaborative activities and their access to (and sharing of) information resources
Enabling Spatio-Temporal Search in Open Data
Intuitively, most datasets found in Open Data are organised by spatio-temporal scope, that is, single datasets provide data for a certain region, valid for a certain time period. For many use cases (such as for instance data journalism and fact checking) a pre-dominant need is to scope down the relevant datasets to a particular period or region. Therefore, we argue that spatio-temporal search is a crucial need for Open Data portals and across Open Data portals, yet - to the best of our knowledge - no working solution exists. We argue that - just like for for regular Web search - knowledge graphs can be helpful to significantly improve search: in fact, the ingredients for a public knowledge graph of geographic entities as well as time periods and events exist already on the Web of Data, although they have not yet been integrated and applied - in a principled manner - to the use case of Open Data search. In the present paper we aim at doing just that: we (i) present a scalable approach to construct a spatio-temporal knowledge graph that hierarchically structures geographical, as well as temporal entities, (ii) annotate a large corpus of tabular datasets from open data portals, (iii) enable structured, spatio-temporal search over Open Data catalogs through our spatio-temporal knowledge graph, both via a search interface as well as via a SPARQL endpoint, available at data.wu.ac.at/odgraphsearch/Series: Working Papers on Information Systems, Information Business and Operation
Narrative Cartography with Knowledge Graphs
Narrative cartography is a discipline which studies the interwoven nature of stories and maps. However, conventional geovisualization techniques of narratives often encounter several prominent challenges, including the data acquisition & integration challenge and the semantic challenge. To tackle these challenges, in this paper, we propose the idea of narrative cartography with knowledge graphs (KGs). Firstly, to tackle the data acquisition & integration challenge, we develop a set of KG-based GeoEnrichment toolboxes to allow users to search and retrieve relevant data from integrated cross-domain knowledge graphs for narrative mapping from within a GISystem. With the help of this tool, the retrieved data from KGs are directly materialized in a GIS format which is ready for spatial analysis and mapping. Two use cases â Magellanâs expedition and World War II â are presented to show the effectiveness of this approach. In the meantime, several limitations are identified from this approach, such as data incompleteness, semantic incompatibility, and the semantic challenge in geovisualization. For the later two limitations, we propose a modular ontology for narrative cartography, which formalizes both the map content (Map Content Module) and the geovisualization process (Cartography Module). We demonstrate that, by representing both the map content and the geovisualization process in KGs (an ontology), we can realize both data reusability and map reproducibility for narrative cartography
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