29,933 research outputs found
Spatio-textual indexing for geographical search on the web
Many web documents refer to specific geographic localities and many
people include geographic context in queries to web search engines. Standard
web search engines treat the geographical terms in the same way as other terms.
This can result in failure to find relevant documents that refer to the place of
interest using alternative related names, such as those of included or nearby
places. This can be overcome by associating text indexing with spatial indexing
methods that exploit geo-tagging procedures to categorise documents with
respect to geographic space. We describe three methods for spatio-textual
indexing based on multiple spatially indexed text indexes, attaching spatial
indexes to the document occurrences of a text index, and merging text index
access results with results of access to a spatial index of documents. These
schemes are compared experimentally with a conventional text index search
engine, using a collection of geo-tagged web documents, and are shown to be
able to compete in speed and storage performance with pure text indexing
To Index or Not to Index: Optimizing Exact Maximum Inner Product Search
Exact Maximum Inner Product Search (MIPS) is an important task that is widely
pertinent to recommender systems and high-dimensional similarity search. The
brute-force approach to solving exact MIPS is computationally expensive, thus
spurring recent development of novel indexes and pruning techniques for this
task. In this paper, we show that a hardware-efficient brute-force approach,
blocked matrix multiply (BMM), can outperform the state-of-the-art MIPS solvers
by over an order of magnitude, for some -- but not all -- inputs.
In this paper, we also present a novel MIPS solution, MAXIMUS, that takes
advantage of hardware efficiency and pruning of the search space. Like BMM,
MAXIMUS is faster than other solvers by up to an order of magnitude, but again
only for some inputs. Since no single solution offers the best runtime
performance for all inputs, we introduce a new data-dependent optimizer,
OPTIMUS, that selects online with minimal overhead the best MIPS solver for a
given input. Together, OPTIMUS and MAXIMUS outperform state-of-the-art MIPS
solvers by 3.2 on average, and up to 10.9, on widely studied
MIPS datasets.Comment: 12 pages, 8 figures, 2 table
Index ordering by query-independent measures
Conventional approaches to information retrieval search through all applicable entries in an inverted file for a particular collection in order to find those documents with the highest scores. For particularly large collections this may be extremely time consuming.
A solution to this problem is to only search a limited amount of the collection at query-time, in order to speed up the retrieval process. In doing this we can also limit the loss in retrieval efficacy (in terms of accuracy of results). The way we achieve this is to firstly identify the most “important” documents within the collection, and sort documents within inverted file lists in order of this “importance”. In this way we limit the amount of information to be searched at query time by eliminating documents of lesser importance, which not only makes the search more efficient, but also limits loss in retrieval accuracy. Our experiments, carried out on the TREC Terabyte collection, report significant savings, in terms of number of postings examined, without significant loss of effectiveness when based on several measures of importance used in isolation, and in combination. Our results point to several ways in which the computation cost of searching large collections of documents can be significantly reduced
Detecting Targets above the Earth's Surface Using GNSS-R Delay Doppler Maps: Results from TDS-1
: Global Navigation Satellite System (GNSS) reflected signals can be used to remotely sense
the Earth’s surface, known as GNSS reflectometry (GNSS-R). The GNSS-R technique has been applied
to numerous areas, such as the retrieval of wind speed, and the detection of Earth surface objects.
This work proposes a new application of GNSS-R, namely to detect objects above the Earth’s surface,
such as low Earth orbit (LEO) satellites. To discuss its feasibility, 14 delay Doppler maps (DDMs) are
first presented which contain unusually bright reflected signals as delays shorter than the specular
reflection point over the Earth’s surface. Then, seven possible causes of these anomalies are analysed,
reaching the conclusion that the anomalies are likely due to the signals being reflected from objects
above the Earth’s surface. Next, the positions of the objects are calculated using the delay and
Doppler information, and an appropriate geometry assumption. After that, suspect satellite objects
are searched in the satellite database from Union of Concerned Scientists (UCS). Finally, three objects
have been found to match the delay and Doppler conditions. In the absence of other reasons for these
anomalies, GNSS-R could potentially be used to detect some objects above the Earth’s surface.Peer ReviewedPostprint (published version
Special Libraries, October 1957
Volume 48, Issue 8https://scholarworks.sjsu.edu/sla_sl_1957/1007/thumbnail.jp
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