Peer-to-peerPeer-to-peer (P2P) computing or networking is a distributed application architecture that partitions tasks or workloads between peers. Peers are equally privileged, equipotent participants in the network. This forms a peer-to-peer network of nodes. Peers make a portion of their resources, such as processing power, disk storage or network bandwidth, directly available to other network participants, without the need for central coordination by servers or stable hosts.
Information retrievalInformation retrieval (IR) in computing and information science is the process of obtaining information system resources that are relevant to an information need from a collection of those resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.
I2PThe Invisible Internet Project (I2P) is an anonymous network layer (implemented as a mix network) that allows for censorship-resistant, peer-to-peer communication. Anonymous connections are achieved by encrypting the user's traffic (by using end-to-end encryption), and sending it through a volunteer-run network of roughly 55,000 computers distributed around the world. Given the high number of possible paths the traffic can transit, a third party watching a full connection is unlikely.
Anonymous P2PAn anonymous P2P communication system is a peer-to-peer distributed application in which the nodes, which are used to share resources, or participants are anonymous or pseudonymous. Anonymity of participants is usually achieved by special routing overlay networks that hide the physical location of each node from other participants. Interest in anonymous P2P systems has increased in recent years for many reasons, ranging from the desire to share files without revealing one's network identity and risking litigation to distrust in governments, concerns over mass surveillance and data retention, and lawsuits against bloggers.
Search engine indexingSearch engine indexing is the collecting, parsing, and storing of data to facilitate fast and accurate information retrieval. Index design incorporates interdisciplinary concepts from linguistics, cognitive psychology, mathematics, informatics, and computer science. An alternate name for the process, in the context of search engines designed to find web pages on the Internet, is web indexing. Popular search engines focus on the full-text indexing of online, natural language documents.
Peer-to-peer file sharingPeer-to-peer file sharing is the distribution and sharing of digital media using peer-to-peer (P2P) networking technology. P2P file sharing allows users to access media files such as books, music, movies, and games using a P2P software program that searches for other connected computers on a P2P network to locate the desired content. The nodes (peers) of such networks are end-user computers and distribution servers (not required).
Document retrievalDocument retrieval is defined as the matching of some stated user query against a set of free-text records. These records could be any type of mainly unstructured text, such as newspaper articles, real estate records or paragraphs in a manual. User queries can range from multi-sentence full descriptions of an information need to a few words. Document retrieval is sometimes referred to as, or as a branch of, text retrieval. Text retrieval is a branch of information retrieval where the information is stored primarily in the form of text.
Content-based image retrievalContent-based image retrieval, also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the problem, that is, the problem of searching for s in large databases (see this survey for a scientific overview of the CBIR field). Content-based image retrieval is opposed to traditional concept-based approaches (see ). "Content-based" means that the search analyzes the contents of the image rather than the metadata such as keywords, tags, or descriptions associated with the image.
Multimedia information retrievalMultimedia information retrieval (MMIR or MIR) is a research discipline of computer science that aims at extracting semantic information from multimedia data sources. Data sources include directly perceivable media such as audio, and video, indirectly perceivable sources such as text, semantic descriptions, biosignals as well as not perceivable sources such as bioinformation, stock prices, etc. The methodology of MMIR can be organized in three groups: Methods for the summarization of media content (feature extraction).
Full-text searchIn text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references). In a full-text search, a search engine examines all of the words in every stored document as it tries to match search criteria (for example, text specified by a user).
