627 research outputs found
Joint Video and Text Parsing for Understanding Events and Answering Queries
We propose a framework for parsing video and text jointly for understanding
events and answering user queries. Our framework produces a parse graph that
represents the compositional structures of spatial information (objects and
scenes), temporal information (actions and events) and causal information
(causalities between events and fluents) in the video and text. The knowledge
representation of our framework is based on a spatial-temporal-causal And-Or
graph (S/T/C-AOG), which jointly models possible hierarchical compositions of
objects, scenes and events as well as their interactions and mutual contexts,
and specifies the prior probabilistic distribution of the parse graphs. We
present a probabilistic generative model for joint parsing that captures the
relations between the input video/text, their corresponding parse graphs and
the joint parse graph. Based on the probabilistic model, we propose a joint
parsing system consisting of three modules: video parsing, text parsing and
joint inference. Video parsing and text parsing produce two parse graphs from
the input video and text respectively. The joint inference module produces a
joint parse graph by performing matching, deduction and revision on the video
and text parse graphs. The proposed framework has the following objectives:
Firstly, we aim at deep semantic parsing of video and text that goes beyond the
traditional bag-of-words approaches; Secondly, we perform parsing and reasoning
across the spatial, temporal and causal dimensions based on the joint S/T/C-AOG
representation; Thirdly, we show that deep joint parsing facilitates subsequent
applications such as generating narrative text descriptions and answering
queries in the forms of who, what, when, where and why. We empirically
evaluated our system based on comparison against ground-truth as well as
accuracy of query answering and obtained satisfactory results
RDF Querying
Reactive Web systems, Web services, and Web-based publish/
subscribe systems communicate events as XML messages, and in
many cases require composite event detection: it is not sufficient to react
to single event messages, but events have to be considered in relation to
other events that are received over time.
Emphasizing language design and formal semantics, we describe the
rule-based query language XChangeEQ for detecting composite events.
XChangeEQ is designed to completely cover and integrate the four complementary
querying dimensions: event data, event composition, temporal
relationships, and event accumulation. Semantics are provided as
model and fixpoint theories; while this is an established approach for rule
languages, it has not been applied for event queries before
Tabulator Redux: writing Into the Semantic Web
A first category of Semantic Web browsers were designed to present a given dataset (an RDF graph) for perusal, in various forms. These include mSpace, Exhibit, and to a certain extent Haystack. A second category tackled mechanisms and display issues around linked data gathered on the fly. These include Tabulator, Oink, Disco, Open Link Software's Data Browser, and Object Browser. The challenge of once that data is gathered, how might it be edited, extended and annotated has so far been left largely unaddressed. This is not surprising: there are a number of steep challenges for determining how to support editing information in the open web of linked data. These include the representation of both the web of documents and the web of things, and the relationships between them; ensuring the user is aware of and has control over the social context such as licensing and privacy of data being entered, and, on a web in which anyone can say anything about anything, helping the user intuitively select the things which they actually wish to see in a given situation. There is also the view update problem: the difficulty of reflecting user edits back through functions used to map web data to a screen presentation. In the latest version of the Tabulator project, described in this paper we have focused on providing the write side of the readable/writable web. Our approach has been to allow modification and addition of information naturally within the browsing interface, and to relay changes to the server triple by triple for least possible brittleness (there is no explicit 'save' operation). Challenges which remain include the propagation of changes by collaborators back to the interface to create a shared editing system. To support writing across (semantic) Web resources, our work has contributed several technologies, including a HTTP/SPARQL/Update-based protocol between an editor (or other system) and incrementally editable resources stored in an open source, world-writable 'data wiki'. This begins enabling the writable Semantic Web
The tractability frontier of well-designed SPARQL queries
We study the complexity of query evaluation of SPARQL queries. We focus on
the fundamental fragment of well-designed SPARQL restricted to the AND,
OPTIONAL and UNION operators. Our main result is a structural characterisation
of the classes of well-designed queries that can be evaluated in polynomial
time. In particular, we introduce a new notion of width called domination
width, which relies on the well-known notion of treewidth. We show that, under
some complexity theoretic assumptions, the classes of well-designed queries
that can be evaluated in polynomial time are precisely those of bounded
domination width
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