Thread Rating:
  • 0 Vote(s) - 0 Average
  • 1
  • 2
  • 3
  • 4
  • 5
Determining Attributes to Maximize Visibility of Objects full report
Post: #1

Determining Attributes to Maximize Visibility of Objects


In recent years, there has been significant interest in the development of ranking functions and efficient top-k retrieval algorithms to help users in ad-hoc search and retrieval in databases (e.g., buyers searching for products in a catalog). We introduce a complementary problem: how to guide a seller in selecting the best attributes of a new tuple (e.g., a new product) to highlight so that it stands out in the crowd of existing competitive products and is widely visible to the pool of potential buyers. We develop several formulations of this problem. Although the problems are NP-complete, we give several exact and approximation algorithms that work well in practice. One type of exact algorithms is based on Integer Programming (IP) formulations of the problems. Another class of exact methods is based on maximal frequent itemset mining algorithms. The approximation algorithms are based on greedy heuristics. A detailed performance study illustrates the benefits of our methods on real and synthetic data.

Presented BY:
Muhammed Miah, Gautam Das, Vagelis Hristidis and Heikki Mannila


I N recent years, there has been significant interest in developing effective techniques for ad-hoc search and retrieval in unstructured as well as structured data re- positories, such as text collections and relational data- bases. In particular, a large number of emerging applica- tions require exploratory querying on such databases; examples include users wishing to search databases and catalogs of products such as homes, cars, cameras, restau- rants, or articles such as news and job ads. Users brows- ing these databases typically execute search queries via public front-end interfaces to these databases. Typical queries may specify sets of keywords in case of text data- bases, or the desired values of certain attributes in case of structured relational databases. The query-answering system answers such queries by either returning all data objects that satisfy the query conditions, or may rank and return the top-k data objects, or return the results that are on the query™s skyline. If ranking is employed, the rank- ing may either be simplistic “ e.g., objects are ranked by an attribute such as Price; or more sophisticated “ e.g., objects may be ranked by the degree of relevance to the query. While unranked retrieval (also known as Boolean Retrieval) is more common in traditional SQL-based data- base systems, ranked retrieval (also known as Top-k Re- trieval) is more common in text databases, e.g. tf-idf rank- ing [28]. Recently there has been widespread interest in developing suitable top-k retrieval techniques even for structured databases [1, 7, 30]. Skyline retrieval semantics is also investigated where a data point is retrieved by a query if it is not dominated by any other data point in all dimensions [4, 19, 22, 25, 29, 31]. In this paper we do not address new search and retrieval techniques that will aid users in effective exploration of such databases. Rather, the focus is on the complemen- tary novel problem of selecting the data to be shown, elaborated as follows.

read full report

Important Note..!

If you are not satisfied with above reply ,..Please


So that we will collect data for you and will made reply to the request....OR try below "QUICK REPLY" box to add a reply to this page
Popular Searches: dr gautam rege, zfs dump extended attributes, project report velocity of moving objects matlab, session description protocol attributes, factors determining demand of a fast moving consumer good like washing machine detergent, visibility block, more visibility boca raton,

Quick Reply
Type your reply to this message here.

Image Verification
Image Verification
(case insensitive)
Please enter the text within the image on the left in to the text box below. This process is used to prevent automated posts.

Possibly Related Threads...
Thread: Author Replies: Views: Last Post
  imouse full report computer science technology 3 3,636 17-06-2016 12:16 PM
Last Post: ashwiniashok
  computer networks full report seminar topics 7 4,904 25-05-2016 02:07 PM
Last Post: dhanyavp
  Implementation of RSA Algorithm Using Client-Server full report seminar topics 6 4,999 10-05-2016 12:21 PM
Last Post: dhanyavp
  Optical Computer Full Seminar Report Download computer science crazy 43 34,287 29-04-2016 09:16 AM
Last Post: dhanyavp
  ethical hacking full report computer science technology 41 46,790 18-03-2016 04:51 PM
Last Post: seminar report asees
  broadband mobile full report project topics 7 2,105 27-02-2016 12:32 PM
Last Post: Prupleannuani
  steganography full report project report tiger 15 19,488 11-02-2016 02:02 PM
Last Post: seminar report asees
  Digital Signature Full Seminar Report Download computer science crazy 20 14,051 16-09-2015 02:51 PM
Last Post: seminar report asees
  Mobile Train Radio Communication ( Download Full Seminar Report ) computer science crazy 10 12,245 01-05-2015 03:36 PM
Last Post: seminar report asees
  service oriented architecture full report project report tiger 12 6,462 27-04-2015 01:48 PM
Last Post: seminar report asees