Showing posts with label android project thesis work. Show all posts

Tuesday, 20 October 2015

A Location- And Diversity-Aware News Feed System for Mobile Users

ABSTRACT

A location-aware news feed (LANF) system generates news feeds for a mobile user based on her spatial preference (i.e., her current location and future locations) and non-spatial preference (i.e., her interest). Existing LANF systems simply send the most relevant geo-tagged messages to their users. Unfortunately, the major limitation of such an existing approach is that, a news feed may contain messages related to the same location (i.e., point-of-interest) or the same category of locations (e.g., food, entertainment or sport). We argue that diversity is a very important feature for location-aware news feeds because it helps users discover new places and activities. In this paper, we propose D-MobiFeed; a new LANF system enables a user to specify the minimum number of message categories (h) for the messages in a news feed. In D-MobiFeed, our objective is to efficiently schedule news feeds for a mobile user at her current and predicted locations, such that (i) each news feed contains messages belonging to at least h different categories, and (ii) their total relevance to the user is maximized. To achieve this objective, we formulate the problem into two parts, namely, a decision problem and an optimization problem. For the decision problem, we provide an exact solution by modeling it as a maximum flow problem and proving its correctness. The optimization problem is solved by our proposed three-stage heuristic algorithm. We conduct a user study and experiments to evaluate the performance of D-MobiFeed using a real data set crawled from Foursquare. Experimental results show that our proposed three-stage heuristic scheduling algorithm outperforms the brute-force optimal algorithm by at least an order of magnitude in terms of running time and the relative error incurred by the heuristic algorithm is below 1%. D-MobiFeed with the location prediction method effectively improves the relevance, diversity, and efficiency of news feeds.

AIM

The aim of this paper is is to efficiently schedule news feeds for a mobile user at her current and predicted locations, such that (i) each news feed contains messages belonging to at least h different categories, and (ii) their total relevance to the user is maximized.

SCOPE

The scope of this paper is to achieve this objective, we formulate the problem into two parts, namely, a decision problem and an optimization problem.

EXISTING SYSTEM

MobiFeed the state-of-the-art location-aware news feed system schedules news feeds for mobile users. In MobiFeed, the relevance of a message m to Bob is measured by both the content similarity between m and Bob’s submitted messages (i.e., a non-spatial factor) and the distance between m and Bob (i.e., a spatial factor). MobiFeed is motivated by the fact that, if the news feeds are only computed based on a user’s location at the query time (i.e., it does not consider the user’s future locations, e.g., GeoFeed), the total relevance of news feeds is not optimized With the geographical distance between a message and a mobile user in a relevance measure model, the relevance of a message to a mobile user is changing as the user is moving. Such a dynamic environment gives us an opportunity to employ location prediction technique to improve the quality of news feeds and the system efficiency. Existing diversification problems focus on retrieving an individual list of items with a certain level of diversity. In contrast, with our location prediction techniques, we aim at improving the quality of news feeds by scheduling multiple location- and diversity-aware news feeds for mobile users simultaneously.

DISADVANTAGES

· A news feed may contain messages related to the same location (i.e., point-of-interest) or the same category of locations (e.g., food, entertainment or sport).

· In MobiFeed considers a mobile environment that makes our location- and diversity-aware news feed system unique and more challenging.

PROPOSED SYSTEM

In this project, propose D-MobiFeed; a new LANF system enables a user to specify the minimum number of message categories (h) for the messages in a news feed. In D-MobiFeed, our objective is to efficiently schedule news feeds for a mobile user at her current and predicted locations, such that (i) each news feed contains messages belonging to at least h different categories, and (ii) their total relevance to the user is maximized. To achieve this objective, we formulate the problem into two parts, namely, a decision problem and an optimization problem. For the decision problem, we provide an exact solution by modeling it as a maximum flow problem and proving its correctness. The optimization problem is solved by our proposed three-stage heuristic algorithm. We conduct a user study and experiments to evaluate the performance of D-MobiFeed using a real data set crawled from Foursquare. Experimental results show that our proposed three-stage heuristic scheduling algorithm outperforms the brute-force optimal algorithm by at least an order of magnitude in terms of running time and the relative error incurred by the heuristic algorithm is below 1%. D-MobiFeed with the location prediction method effectively improves the relevance, diversity, and efficiency of news feeds.

ADVANTAGES

· D-MobiFeed with the location prediction method effectively improves the relevance, diversity, and efficiency of news feeds.

· D-MobiFeed can efficiently provide location- and diversity-aware news feeds when maintaining their high quality in terms of relevance

SYSTEM ARCHITECTURE:

SYSTEM CONFIGURATION

HARDWARE REQUIREMENTS:-

· Processor - Pentium –III

· Speed - 1.1 Ghz

· RAM - 256 MB(min)

· Hard Disk - 20 GB

· Floppy Drive - 1.44 MB

· Key Board - Standard Windows Keyboard

· Mouse - Two or Three Button Mouse

· Monitor - SVGA

SOFTWARE REQUIREMENTS:-

· Operating System : Android OS

· Front End : JAVA

· Database : Sqlite

· Tool :Eclipse

REFERENCES

Chow, C.Xu, W. “A Location- and Diversity-aware News Feed System for Mobile Users” IEEE Transactions ON Services Computing, Volume PP, Issue 99 MAY 2015.

CONTEXT-BASED ACCESS CONTROL SYSTEMS FOR MOBILE DEVICES

ABSTRACT:

Mobile Android applications often have access to sensitive data and resources on the user device. Misuse of this data by malicious applications may result in privacy breaches and sensitive data leakage. An example would be a malicious application surreptitiously recording a confidential business conversation. The problem arises from the fact that Android users do not have control over the application capabilities once the applications have been granted the requested privileges upon installation. In many cases, however, whether an application may get a privilege depends on the specific user context and thus we need a context-based access control mechanism by which privileges can be dynamically granted or revoked to applications based on the specific context of the user. In this paper we propose such an access control mechanism. Our implementation of context differentiates between closely located sub-areas within the same location. We have modified the Android operating system so that context-based access control restrictions can be specified and enforced. We have performed several experiments to assess the efficiency of our access control mechanism and the accuracy of context detection.

AIM

The aim of this paper is our implementation of context differentiates between closely located sub-areas within the same location.

SCOPE

The scope of this paper tends to have performed several experiments to assess the efficiency of our access control mechanism and the accuracy of context detection.

EXISTING SYSTEM:

Security for mobile operating systems focuses on restricting applications from accessing sensitive data and resources, but mostly lacks efficient techniques for enforcing those restrictions according to fine-grained contexts that differentiate between closely located subareas. Moreover, most of this work has focused on developing policy systems that do not restrict privileges per application and are only effective system-wide. So User disable all applications from using the camera and any device resources and privileges that employers restrict while at work, while the user device can retain all its original privileges outside the work area.

DISADVANTAGES

· Do not cover all the possible ways in which applications can access user data and device resources.

· The User leakage of Their privacy.

· Existing location-based policy systems are not accurate enough to differentiate between nearby locations without extra hardware or location devices.

PROPOSED SYSTEM:

In this paper, we propose a context-based access control (CBAC) mechanism for Android systems that allows smartphone users to set configuration policies over their applications’ usage of device resources and services at different contexts. Through the CBAC mechanism, users can, for example, set restricted privileges for device applications when using the device at work, and device applications may re-gain their original privileges when the device is used at home. This change in device privileges is automatically applied as soon as the user device matches a pre-defined context of a user-defined policy. The user can also specify a default set of policies to be applied when the user is located in a non-previously defined location. Configured policy restrictions are defined according to the accessible device resources, services, and permissions that are granted to applications at installation time. Such policies define which services are offered by the device and

limit the device and user information accessibility. Policy restrictions are linked to context and are configured by the device user. We define context according to location and time.