Different search approaches

Noggle Search Approaches

There are different ways how Noggle helps to find documents. The main approaches can be described in the following categories:

Text queries

1. Searching documents based on text queries
This is the standard way of how search requests work in the web or on google: Put your search string in the input box and noggle will present the found documents based on relevance ranking in the output window.

KnowledgeMap cluster queries

2. Searching documents based on KnowledgeMap clusters
This approach is used if you are not sure about the concrete term or search string you need to search for. So you start with just a generic search string which you put in the search text box. As a result, noggle will present a large list of documents which might match the generic top-level word search. Now, to narrow down your search, you can build a so-called “noggle map” which clusters found documents based into linguistic clusters. These clusters will be presented visually. Now, you can select one or more clusters which come more close to your topic you are looking for and press the “NoggleCluster” search button. Now a new search request is performed to just search for content in the selected clusters. Afterwards, the found documents will again be clustered based on linguistic patterns. This process can now be repeated to slice and dice the available content into categories which are automatically generated based on the content until you have found a cluster with documents that have a high relevance to your individual knowledge you are looking for.

“Similar like this” search

3. Searching documents with the “similar like this” function
Another important way of searching documents is that you need to check “similar” documents once you have found once document of interest. So if you have found one document that matches your area of interest, you can select this document and perform a “similar like this” search request within all available libraries. This way, noggle will now check which documents have a “similar” content like the selected one and will present all documents which have a content-wise correlation to the select document. This feature is really great because it can find similar document across different libraries. So if John has a project document with interesting content, just select this document, perform a “similar like this request” and noggle will check if you other peers/libraries contain similar documents. It is similar to what you know from “Amazon” – once you have selected a book, Amazon will present a list of similar books which you might like based on the content of the books. Bring this power now directly to your desktop. Let noggle recommend documents that might be interesting for you based on the one document you selected.

“Drop-in” search

4.Searching documents with the “drop-in” area
This is another use-case often needed for the knowledge worker: Think about a situation when you receive a document via eMail. Now you think “Hmmm, I think I have some similar documents with additional content, havent I or a colleague?”. Now you can drag’n drop the document from your eMail inbox directly on the “drop-in” window area in the Noggle client. Noggle will instantly run the indexing service on the document and instantly check all available libraries for “similar” documents. So within milliseconds, Noggle will present you a list with documents in your libraries, which a similar to the dragged document. Even if the document is not present in any library, it can be used to search similar documents in all libraries available. In addition, it will automatically perform an “expert” search. This means that in addition to the similar documents list, you automatically get a list of peers/experts which have a similar knowledge profile to the document your dropped on the application. And all of this happens in near-realtime instantly on your desktop.

What is a noggle library?

What is a noggle library?

The Noggle library functions are based on Lucene, an open source, highly scalable text search-engine library available from the Apache Software Foundation. Web sites like Wikipedia and LinkedIn have been powered by Lucene.

Noggle brings the best availabe search and indexing technology right to your desktop, the Noggle App.

Based on Lucene in the back, Noggle is able to achieve fast search responses because, instead of searching the text directly, it searches an index instead – the “noggle library”. This would be the equivalent of retrieving pages in a book related to a keyword by searching the index at the back of a book, as opposed to searching the words in each page of the book.

Noggle library tools focus mainly on text indexing and searching. It is the core element that is used to build different search capabilities. Based on Lucene, the noggle library core has many features. It:

  • Has powerful, accurate, and efficient search algorithms.
  • Calculates a score for each document that matches a given query and returns the most relevant documents ranked by the scores.
  • Supports many powerful query types, such as PhraseQuery, WildcardQuery, RangeQuery, FuzzyQuery, BooleanQuery, and more.
  • Supports parsing of human-entered rich query expressions.
  • Allows users to extend the searching behavior using custom sorting, boosting and extending search ideas.
  • Uses a file-based locking mechanism to prevent concurrent index modifications.
  • Allows searching and indexing simultaneously.

The Noggle library core lets you index any data available in textual format. Therefore, Noggle uses pre-processing and parsing techniques to extract the plain text from different source formats like Word, PowerPoint, Excel, PDF files and other formats. Noggle can be used with almost any data source as long as textual information can be extracted from it. The first step of noggle before building the library by indexing the data is to make it available in simple text format. Noggle uses custom parsers and data converters; mainly based on the Microsoft IFilter technology.

Indexing is a process of converting text data into a format that facilitates rapid searching. A simple analogy is an index you would find at the end of a book: That index points you to the location of topics that appear in the book.

Noggle stores the input data in a data structure called an inverted index, which is stored on the file system or memory as a set of index files. Most Web search engines use an inverted index. It lets users perform fast keyword look-ups and finds the documents that match a given query. Before the text data is added to the index, it is processed by an custom noggle analyzer.

The analyzer is converting the text data into a fundamental unit of searching, which is called as term. During analysis, the text data goes through multiple operations: extracting the words, removing common words, ignoring punctuation, reducing words to root form, changing words to lowercase, etc. Analysis happens just before indexing and query parsing. Analysis converts text data into tokens, and these tokens are added as terms in the Noggle library index.

As a result, a high-performant library is created which can be shared with your peers to execute search request in milliseconds over the full content. The indexing and library building process is not only providing fast search results – it also provides relevant ranking scores back to the search results.

Once your decide to share a noggle library with one of your peers, the library will be encrypted and obfuscated once it leaves your client to the noggle network. Only the named peer is available to decrypt the library – so your library is always secure in the noggle network.

Where are your servers located?

Our servers are operated in datacenters within the EU.

Please read our security guidelines for more information on security.

Security Guidelines

Is it a peer-to-peer file sharing tool?

To make it short: No. Noggle is NOT a peer-to-peer file sharing software. You can not share file or documents directly with noggle.

Noggle sets a library management toolset on top of your documents. This library management helps to make your documents or files searchable. You can share the created library information with your private experts, partners or colleagues (“peers”). After you shared a library, your peers are able to search and locate documents that are stored on your local accessible storages – but they are not able to access the document itself. The library makes your content findable by others. And you define who is able to get your library. So your colleagues can search and find documents they dont have access to, but you want your peers being able to find documents you have. The library management toolset makes your documents findable without the need to share documents or change access rights. Once a peer has found an relevant document that is located in one of your libraries, they can request to get access to the document. But you decide, case by case, if you want to share the document itself. Noggle does not provide access to your documents for your peers.

Saied this, we use the peer-to-peer technology to create a secure managed network where each user is able to build libraries and share the library information with dedicated, named peers. This allows an easy way to share, find and locate relevant content. The managed service only provides security. The user decides and controlls everything. Noggle only provides the managed service to connect dedicated peers. There is no central instance which is doing search and returning search requests. Everything happens on the client side and everything that leaves your client is encrypted until it reaches the peer client you have defined.

Each client will not act as a server. The client only communicates with the noggle network to provide and receive encrypted library information that is shared with named peers.

Can you explain how it works?

Noggle – How It Works

Please review the following 5 min. info video:

 Features Summary Article

You can download a features summary article here:

Download Article

Where to download the App?

It is possible the download the application from our website or alternative download locations:

Download Links

Windows 10 Version:
Noggle Windows 10 Store: Windows 10 Store Download

Windows 7: 
Noggle Direct Download: Download Link 1

External Links:
CNET Download: Download Link 2

What is noggle? A Document Management Tool. Stop Searching

Summary

The application provides methods and tools for indexing and for searching documents across a plurality of storage locations and client devices.

Many situations exist in which multiple users generate electronic files on a plurality of client computers that are connected to a network. The users frequently store their files locally on different storage locations only accessible via their local client computers. Locally stored files are generally not accessible to other users, causing duplication of work and other inefficiencies that could be avoided, if users were able to locate files on other user’s devices.

Noggle is a solution to provide a managed distributed search functionality to find documents within your knowledge peers. Like a document management tool.

Facts & Features

Noggle is a managed peer-to-peer knowledge network and document management tool. Noggle is not a peer-to-peer file sharing software. Noggle is providing the following key features:

  • Local library builder to search documents on all accessible file and cloud shares
  • Secure managed library sharing services – let others find what you have, find what others have; connect your content with your peers without the need to share documents or modify access rights
  • KnowledgeMap – Search for topics where you are not sure about the exact phrase, let noggle cluster relevant documents based on linguistic patters – find what is relevant; not the exact phrase you searched for
  • KnowlegeMap cluster search – select different clusters from the knowledge map to drill-down into your topic of interest
  • Request documents from your peers – directly request found documents from your peers without the need to leave the client “1 single place for everything”
  • Find documents “like this” – if you have found a first document in the area of you interest, use “find similar” to find all documents within all peer libraries that have similar content to the selected one
  • Expert search function – noggle can find experts for documents based on the content and link to their profiles; including geolocation services; connect with people, not only content
  • Create your own knowledge profile based on documents to create your own expert profile to get found by noggle – Others are able to find you based on their local documents!
  • Drop-In search – DragnDrop a document onto the window – noggle will automatically present all similar documents and present experts with a profile matching the document content

 

Noggle does that for you…

Enables Easy and Efficient Document Searches

Noggle makes distributed and local information retrieval on your desktop as easy as googling public content on the Internet.

Establishes a Trustworthy Information-Exchange Environment

Noggle treats your content as private and follows the highest standards in creating a trusted network for your knowledge peers and others across the organization.

Connects to Knowledge and People

When you search, you are not looking for documents, you are looking for answers. Noggle focuses on finding the experts behind a document and enabling you to connect you with them.

Provides an Instant Response

Noggle allows you to run a knowledge search whenever you need information using its distributed search function conveniently from your desktop.

Provides All Functions through One Easy-to-Use Application

The Noggle App provides in one place all the elements you need to search, distribute, connect, sync, and retrieve.

Eliminates the Need for Supervision

Noggle functions as a decentralized, managed peer-to-peer library and expert retrieval network. No central entity exists that needs to be managed or that decides who can see what. You control local access rights.

Puts Security First and Foremost

Security and data protection is our first priority. Everything that leaves the client is encrypted using the highest standards. Noggle guarantees end-to-end encryption from clients to dedicated peers.

Download Full Overview Article

Download Document Management Tool Feature Overview

Presentation Slides

You can download and review the basic presentation slides here:

Download Presentation

Text Search: Querry Syntax

Text Search: Querry Syntax


This article describes how to structure direct text search requests.

Fields


When performing a search you can either specify a field, or use the default field “Text”. You can search any field by typing the field name followed by a colon “:” and then the term you are looking for.
As an example, let’s assume the library index contains two fields, file and text and text is the default field. If you want to find the document entitled “The Right Way” which contains the text “don’t go this way”, you can enter:

File:”Presentation xyz” AND Text:go
or
File:”Presentation xyz” AND right

Since text is the default field, the field indicator is not required.

Note: The field is only valid for the term that it directly precedes, so the query

File:Presentation xyz right

Will only find “Presentation” in the title field. It will find “xyz” and “right” in the default field (in this case the text field).

Wildcard Searches


To perform a single character wildcard search use the “?” symbol. To perform a multiple character wildcard search use the “*” symbol.
The single character wildcard search looks for terms that match that with the single character replaced. For example, to search for “text” or “test” you can use the search:

te?t

Multiple character wildcard searches looks for 0 or more characters. For example, to search for test, tests or tester, you can use the search:

test*

You can also use the wildcard searches in the middle of a term.
te*t

Note: You can only use a * or ? symbol as the first character of a search if activated in the settings menu.

Fuzzy Searches


Fuzzy searches are based on the Levenshtein Distance, or Edit Distance algorithm. To do a fuzzy search use the tilde, “~”, symbol at the end of a Single word Term. For example to search for a term similar in spelling to “roam” use the fuzzy search:

roam~

This search will find terms like foam and roams.

An additional (optional) parameter can specify the required similarity. The value is between 0 and 1, with a value closer to 1 only terms with a higher similarity will be matched. For example:
roam~0.8

The default that is used if the parameter is not given is 0.5.

Proximity Searches


Finding words are a within a specific distance away. To do a proximity search use the tilde, “~”, symbol at the end of a Phrase. For example to search for “transform” and “infrastructure” within 10 words of each other in a document use the search:

“transform infrastructure”~10

Range Searches


Range Queries allow one to match documents whose field(s) values are between the lower and upper bound specified by the Range Query. Range Queries can be inclusive or exclusive of the upper and lower bounds. Sorting is done lexicographically.
LastModified is saved in the sortable string format ISO 8601.

Therefore you can apply range searches to the LastWriteTime field. Format: yyyy-MM-ddTHH:mm:ss

+LastModified:[2014 TO 2015?]

This will find documents whose LastWriteTime fields have values between 2014 and 2015, inclusive. Note that Range Queries are not reserved for date fields. You could also use range queries with non-date fields:

File:{Aida TO Carmen}

This will find all documents whose file names are between Aida and Carmen, but not including Aida and Carmen.
Inclusive range queries are denoted by square brackets. Exclusive range queries are denoted by curly brackets.

Boosting a Term


Providing the relevance level of matching documents based on the terms found. To boost a term use the caret, “^”, symbol with a boost factor (a number) at the end of the term you are searching. The higher the boost factor, the more relevant the term will be.
Boosting allows you to control the relevance of a document by boosting its term. For example, if you are searching for

transform IT

and you want the term “transform” to be more relevant boost it using the ^ symbol along with the boost factor next to the term. You would type:

transform^4 IT

This will make documents with the term transform appear more relevant. You can also boost Phrase Terms as in the example:

“transform IT”^4 “Infrastructure”

By default, the boost factor is 1. Although the boost factor must be positive, it can be less than 1 (e.g. 0.2)

Boolean Operators


Boolean operators allow terms to be combined through logic operators. Supporting AND, “+”, OR, NOT and “-” as Boolean operators (Note: Boolean operators must be ALL CAPS).
The OR operator is the default conjunction operator. This means that if there is no Boolean operator between two terms, the OR operator is used. The OR operator links two terms and finds a matching document if either of the terms exist in a document. This is equivalent to a union using sets. The symbol || can be used in place of the word OR.
To search for documents that contain either “transform IT” or just “transform” use the query:

“transform IT” transform

or

“transform IT” OR transform

AND

The AND operator matches documents where both terms exist anywhere in the text of a single document. This is equivalent to an intersection using sets. The symbol && can be used in place of the word AND.
To search for documents that contain “transform IT” and “Infrastructure” use the query:

“transform IT” AND “Infrastructure”

+

The “+” or required operator requires that the term after the “+” symbol exist somewhere in a field of a single document.
To search for documents that must contain “transform” and may contain “infrastructure” use the query:

+transform infrastructure

NOT

The NOT operator excludes documents that contain the term after NOT. This is equivalent to a difference using sets. The symbol ! can be used in place of the word NOT.
To search for documents that contain “transform IT” but not “Infrastructure” use the query:

“transform IT” NOT Infrastructure

Note: The NOT operator cannot be used with just one term. For example, the following search will return no results:
NOT “Infrastructure”

The “-” or prohibit operator excludes documents that contain the term after the “-” symbol.
To search for documents that contain “transform IT” but not “Infrastructure” use the query:

“transform IT” -Infrastructure

Grouping


Use parentheses to group clauses to form sub queries. This can be very useful if you want to control the boolean logic for a query.
To search for either “transform” or “IT” and “infrastructure” use the query:

(transform OR IT) AND infrastructure

This eliminates any confusion and makes sure you that website must exist and either term transform or IT may exist.

Field Grouping


Using parentheses to group multiple clauses to a single field.
To search for a text that contains both the word “IT” and the phrase “infrastructure provider” use the query:

Text:(+IT +”infrastructure provider”)

Escaping Special Characters


Escaping special characters that are part of the query syntax. The current list special characters are
+ – && || ! ( ) { } [ ] ^ ” ~ * ? :

To escape these character use the before the character. For example to search for (1+1):2 use the query:
(1+1):2