48,359 research outputs found
Applying Model Checking Techniques to Temporal Queries over WorldWideWeb
We propose an idea of the use of temporal logic formula for the investigation of the World Wide Web(WWW). Semantic Web is known as a next generation web technology, and constructed over RDF formula. The semantics of RDF is given by Knowledge Interchange Format which expressive power is equal to the First Order Logic (FOL). Because the expressive power of the general FOL is not enough for describing temporal properties, we extend the FOL to FO^2 or to other useful temporal logics using the Kripke Structure extracted from RDF documents. The maximum advantage of our method is to provide the means for queries of database system using rich, powerful temporal operators, and also give guarantees of correctness of a system if the system passed examinations imposed by model checking about temporal properties of systems
On Reasoning with RDF Statements about Statements using Singleton Property Triples
The Singleton Property (SP) approach has been proposed for representing and
querying metadata about RDF triples such as provenance, time, location, and
evidence. In this approach, one singleton property is created to uniquely
represent a relationship in a particular context, and in general, generates a
large property hierarchy in the schema. It has become the subject of important
questions from Semantic Web practitioners. Can an existing reasoner recognize
the singleton property triples? And how? If the singleton property triples
describe a data triple, then how can a reasoner infer this data triple from the
singleton property triples? Or would the large property hierarchy affect the
reasoners in some way? We address these questions in this paper and present our
study about the reasoning aspects of the singleton properties. We propose a
simple mechanism to enable existing reasoners to recognize the singleton
property triples, as well as to infer the data triples described by the
singleton property triples. We evaluate the effect of the singleton property
triples in the reasoning processes by comparing the performance on RDF datasets
with and without singleton properties. Our evaluation uses as benchmark the
LUBM datasets and the LUBM-SP datasets derived from LUBM with temporal
information added through singleton properties
Ranking Archived Documents for Structured Queries on Semantic Layers
Archived collections of documents (like newspaper and web archives) serve as
important information sources in a variety of disciplines, including Digital
Humanities, Historical Science, and Journalism. However, the absence of
efficient and meaningful exploration methods still remains a major hurdle in
the way of turning them into usable sources of information. A semantic layer is
an RDF graph that describes metadata and semantic information about a
collection of archived documents, which in turn can be queried through a
semantic query language (SPARQL). This allows running advanced queries by
combining metadata of the documents (like publication date) and content-based
semantic information (like entities mentioned in the documents). However, the
results returned by such structured queries can be numerous and moreover they
all equally match the query. In this paper, we deal with this problem and
formalize the task of "ranking archived documents for structured queries on
semantic layers". Then, we propose two ranking models for the problem at hand
which jointly consider: i) the relativeness of documents to entities, ii) the
timeliness of documents, and iii) the temporal relations among the entities.
The experimental results on a new evaluation dataset show the effectiveness of
the proposed models and allow us to understand their limitation
Why People Search for Images using Web Search Engines
What are the intents or goals behind human interactions with image search
engines? Knowing why people search for images is of major concern to Web image
search engines because user satisfaction may vary as intent varies. Previous
analyses of image search behavior have mostly been query-based, focusing on
what images people search for, rather than intent-based, that is, why people
search for images. To date, there is no thorough investigation of how different
image search intents affect users' search behavior.
In this paper, we address the following questions: (1)Why do people search
for images in text-based Web image search systems? (2)How does image search
behavior change with user intent? (3)Can we predict user intent effectively
from interactions during the early stages of a search session? To this end, we
conduct both a lab-based user study and a commercial search log analysis.
We show that user intents in image search can be grouped into three classes:
Explore/Learn, Entertain, and Locate/Acquire. Our lab-based user study reveals
different user behavior patterns under these three intents, such as first click
time, query reformulation, dwell time and mouse movement on the result page.
Based on user interaction features during the early stages of an image search
session, that is, before mouse scroll, we develop an intent classifier that is
able to achieve promising results for classifying intents into our three intent
classes. Given that all features can be obtained online and unobtrusively, the
predicted intents can provide guidance for choosing ranking methods immediately
after scrolling
Feeds as Query Result Serializations
Many Web-based data sources and services are available as feeds, a model that
provides consumers with a loosely coupled way of interacting with providers.
The current feed model is limited in its capabilities, however. Though it is
simple to implement and scales well, it cannot be transferred to a wider range
of application scenarios. This paper conceptualizes feeds as a way to serialize
query results, describes the current hardcoded query semantics of such a
perspective, and surveys the ways in which extensions of this hardcoded model
have been proposed or implemented. Our generalized view of feeds as query
result serializations has implications for the applicability of feeds as a
generic Web service for any collection that is providing access to individual
information items. As one interesting and compelling class of applications, we
describe a simple way in which a query-based approach to feeds can be used to
support location-based services
Reactivity on the Web
Reactivity, the ability to detect simple and composite events and respond in a timely
manner, is an essential requirement in many present-day information systems. With
the emergence of new, dynamic Web applications, reactivity on the Web is receiving
increasing attention. Reactive Web-based systems need to detect and react not only
to simple events but also to complex, real-life situations. This paper introduces
XChange, a language for programming reactive behaviour on the Web, emphasising
the querying of event data and detection of composite events
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