You are reading the article Google Says ‘Discovered – Currently Not Indexed’ Status Can Last Forever updated in December 2023 on the website Daihoichemgio.com. We hope that the information we have shared is helpful to you. If you find the content interesting and meaningful, please share it with your friends and continue to follow and support us for the latest updates. Suggested January 2024 Google Says ‘Discovered – Currently Not Indexed’ Status Can Last Forever
This is stated during the Google Search Central SEO office-hours hangout recorded on February 18.
An individual named Davor Bobek joins the livestream to ask Google’s Search Advocate John Mueller about the ‘Discovered – Currently not indexed’ message and how long it can be expected to last.
That message means the page was found by Google, but not crawled yet.
There are various reasons why Google wouldn’t crawl a page, despite knowing it exists.
It could be due to technical reasons. Google may have tried to crawl the URL but the site was overloaded. If that’s the case then Google will reschedule the crawl for a later date.
Another reason for the ‘Discovered – Currently not indexed’ message could be because the website doesn’t meet a certain threshold for quality, in Google’s view.
Google doesn’t make any guarantees to crawl and index every webpage.
Even though Google is one of the biggest companies in the world, it has finite resources when it comes to computing power.
The computing resources Google uses to crawl the web are reserved for websites considered valuable and high quality.
To that end, the ‘Discovered – Currently not indexed’ status can possibly last forever.
Mueller says as much in his response, which you can read in the next section.
Google Index Coverage Report: ‘Discovered – Currently Not Indexed’When asked how long webpages can remain discovered but not indexed, Mueller says:
“That can be forever. It’s something where we just don’t crawl and index all pages. And it’s completely normal for any website that we don’t have everything indexed.
And, especially with a newer website if you have a lot of content, then I would assume it’s expected that a lot of the new content for a while will be discovered and not indexed.
And then over time usually it kind of shifts over, like well it’s actually crawled, or it’s actually indexed, when we see that there’s actually value in focusing more on the website itself. But it’s not guaranteed.”
So, what can you do if you have a number of pages that Google has discovered but not indexed?
Rather than leaving the content as-is and hoping it will get indexed one day, you should continue working on your website to improve its overall quality.
Mueller continues:
“So from that point of view it’s not that I would say you should just wait a little bit and suddenly things will get better with crawling and indexing. It’s more that, like continue working on the website and making sure that our systems recognize that there’s value in crawling and indexing more and then over time we will crawl and index more.”
Hear Mueller’s full response in the video below.
For more insight into how quality issues can prevent content from getting indexed, see the following articles:
Featured Image: IB Photography/Shutterstock
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Shiny Pokemon Go Hunting Glitch Discovered At Last
Shiny Pokemon GO hunting glitch discovered at last
There’s a bit of a glitch in Pokemon GO that’s not a big enough deal for Niantic to “fix”. This glitch is nicknamed “Skip Catch”, and it’s pretty much exactly what you’d expect – it skips the lengthy process of waiting for each Pokemon to wiggle around and either escape or remain in your care forevermore. You’re going to need two hands to do this method, which is a bit of work, but it’s worth the effort if you’re looking for Shiny Pokemon en masse.
The Shiny Pokemon hunt in Pokemon GO rages on! After thousands of catches and dozens of Shiny Pokemon – dozens! – the strategy remains largely the same. Catch as many of one Pokemon as you can, and provided there IS a Shiny of said Pokemon, a shiny you may find! To make this method slightly less maddening that it inevitably turns out to be, the Skip Catch glitch is key.
NOTE: The image at the top of the article was sorta vandalized by SlashGear (in a positive, supportive way!) And was originally illustrated by Sarah Richford. More information on this stack of Mudkips can be found at the Sarah Richfords DeviantArt page.
To make this Skip Glitch action yours, you’ll need to follow the following instructions in either the Android or iOS version of Pokemon GO. Make sure you’re seeking out a Pokemon that actually has a Shiny version in the game before you use this method 12,000 times, if you’re looking specifically for Shinies, but feel free to use the method for whatever sort of Pokemon you like – it’s good for all! The instructions are followed by a helpful instructional video from the folks at BitRulez.
• Step 1: In a Pokemon encounter, swipe over your Pokeball, right to left, and keep your finger on the screen (don’t lift up yet!)• Step 2: Throw the Pokeball with your free hand (like normal) while keeping your Step 1 finger pressed on the screen.• Step 3: Once the Pokeball has hit the Pokemon (Nice!) you’ll remove your Step 1 finger from the screen.• Step 4: As the Pokemon is being kidnapped by the Pokeball, you should see your drawer full of Pokeballs jump out from the right side of your display.• Step 5: Tap your display once.• Step 6: Tap your escape button (run away) in the upper left-hand corner of your screen.• Step 7: Repeat at will. If you captured the Pokemon, you’ll see some sort of ERROR message (don’t worry, nothing bad happened to you or your Pokemon). Otherwise you can try again!
If you captured the Pokemon successfully, you’ll likely find an ERROR 55. If you did not, you’ll be given the opportunity to move in and out of the capture screen far more quickly than you’d have gone without the Skip Catch method. Have a peek at the timeline below and prepare your mind and your soul to capture as many Mudkips as possible in July. The big event is nearly here, and a Shiny Mudkip shall be yours.
George W. Bush Not ‘Miserable Failure” Says Aol
Currently, on Google the top four results for “miserable failure” are:
www.whitehouse.gov/president/gwbbio.html – 29k – Cached – Similar pages
www.whitehouse.gov/history/presidents/jc39.html – 36k – Cached – Similar pages
clinton.senate.gov/ – 9k – 5 Feb 2004 – Cached – Similar pages
However, according to an article in the Direct Marketing News, the results for the same search on AOL (which as stated above uses Google for their results) does not list the George W. Bush page. Most interesting.
DMNews explains:
The links to the political figures’ sites appeared after a group of Webloggers last year began to link to Bush’s bio on Web pages with the words “miserable failure.” Bush partisans followed suit to include liberal political figures like Moore, Clinton and Carter.
AOL, which displays search results by Google, said it removed the link to Bush’s Web site under its policy to take out obviously irrelevant results.
AOL did not explain why Bush’s site qualified as link spam while those of Moore, Clinton and Carter did not, but said it would stop judging individual links.
What is Google Bombing?
—Google bomb n.
Example Citation:
Here are four types of Google Bombs whose fuses have already been lit:
1. Humor Bombs. Mathes’ original Google Bomb remains the classic of this genre. It’s pretty funny to see your friend come up in Google as the No. 1 talentless hackin the whole world. Successful humor bombs, like most Google Bombs, require search key words that don’t get a lot of traffic.
—John Hiler, “Google Time Bomb,” Slate Magazine, March 25, 2002
Examples of Google Bombs:
Search on these terms for influenced Google Bomb results:
“Miserable Failure”
“Weapons of Mass Destruction”
“great president”
This is not the first time AOL has been accused of censoring their network for political reasons.
In 2000, CNET News reported that AOL’s “youth filters” were preventing young surfers from accessing liberal websites; “your children can easily view the site of the Republican National Committee,” Brian Livingston reported at the time, “but the Democratic National Committee is blocked.”
According to chúng tôi AOL and its chat moderators have also previously closed or hidden anti-Bush chatrooms:
As I finished browsing the usual progressive and leftist websites on the internet, I became curious to search the AOL Chatroom listings. One of the public chatrooms I entered was titled, ‘Bush 4 Imprisonment.’ There were four other screen names in the chatroom when I arrived. We started discussing Bush and the 2004 election.
Our chatroom was still alive and in a deep discussion, but it was like it never existed. This prevented other people from entering or acknowledging that we even had a room. I waited a few minutes and then searched again; the chat room didn’t exist. Which was funny because there were 3 members still conversing in the room.
When such a chatroom is created, and it reaches an AOL Moderator’s attention, it won’t be long until it is silenced.
Wearables Addictive And Unstoppable Says Google X’S Mary Lou Jepsen
Wearables addictive and unstoppable says Google X’s Mary Lou Jepsen
Wearable computing is an unstoppable, addictive force that could well step in to address neurodegenerative illnesses where medicine cannot, Google X’s Mary Lou Jepsen says, though the display division chief refuses to be drawn on what her team is working on inside the clandestine lab. “It’s coming. I don’t think it’s stoppable” Jepsen said of wearables like Google’s Glass which she wore round her neck while speaking at MIT’s EmTech conference on Thursday. However while it may be inescapable, Jepsen still can’t tell us about her particular role in the future; “Sergey insists” on continued secrecy around her project, she explained, referring to Google X lab overseer and Google co-founder Sergey Brin.
Jepsen’s background was already in game-changing hardware. As well as co-founding the One Laptop Per Child (OLPC) project, which aims to bring affordable computing equipment to both developing nations and classrooms closer to home – most recently with the XO Tablet – the display expert founded Pixel Qi, arguably the most successful transflective LCD manufacturer. Pixel Qi products not only work as regular LCDs in normal lighting, but can be used in high-contrast mode outdoors in bright sunlight or when minor power consumption is required.
She joined Google X earlier this year, as “Head of the Display Division”, working on Google’s so-called “moonshot” projects like self-driving autonomous cars which are not so directly connected to the bottom line as products like search, Gmail, and AdWords.
Jepsen is clearly convinced by wearables such as Glass. Describing them as “a way of amplifying you”, much in the same way that she for a long time felt that her laptop was an extension of her mind, the benefit from wearable tech is that it “lets you do more, fast and easily” she suggests. In fact, “you become addicted to the speed of it” Jepsen warned, not only for more everyday tasks like taking photos, but one day for helping people with memory loss and similar conditions.
In ten years for instance, Jepsen predicted, wearables like Glass will be able to quickly identify those people around you, which the exec pointed out would be a real benefit to people with Alzheimer’s among others. That’s assuming Google can get past the privacy concerns; at the moment, the company has said it will not allow face-recognition on Glass until those worries are settled.
Although wearables may end up being ubiquitous, that doesn’t mean that we’ll all be wearing Glass – or, indeed, hardware that looks like anybody else’s – Jepsen claims. As well as her opinion that a range of choice in the design of any body-worn gadget is essential if they’re to be commercially successful, given users will approach them as they do their personal taste in clothing and accessories, she suggested that physical and UI design are only part of a challenge in the segment that’s still yet to be addressed.
The current Glass Explorer Edition is offered in five colors, ranging from the more discrete black through to bright tangerine orange and “sky” blue. That, Google’s Isabelle Olssen, lead industrial designer on the wearable, said at the company’s own I/O conference, was because a single color was deemed too restrictive given Glass’ requirement to “satisfy different personalities.”
Future iterations, such as perhaps the consumer model which Google has suggested is on track for a 2014 release, could even be modular so as to be more flexible or scalable in how they integrate with whatever else the user is wearing.
That need for prior consideration of how a product will scale once launched is something Jepsen touched upon during her talk. In fact, she argued, it’s vital that it’s understood from very early on in the product-development cycle.
As for what Jepsen’s team in particular is working on, that might be rolled out into the public eye in 2014. The division is “maybe sleeping three hours a night to bring the technology forward” but, as with other Google X projects, Brin had sworn her and the others to secrecy in the meantime.
IMAGE CDernbach
Currently, This Hardware Device Is Not Connected To The Computer (Code 45)
Currently, This Hardware Device is Not Connected to The Computer (Code 45) Find out the most effective solutions, tried and tested by our experts
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Code 45 Hardware device is not connected shows when you try accessing a device that is physically connected, but Windows cannot recognize it.
The
code 45 error in Windows 10 can also be caused by corrupt Windows registry keys, outdated device drivers, or faulty hardware.
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INSTALL BY CLICKING THE DOWNLOAD FILE
To fix Windows PC system issues, you will need a dedicated tool
Fortect is a tool that does not simply cleans up your PC, but has a repository with several millions of Windows System files stored in their initial version. When your PC encounters a problem, Fortect will fix it for you, by replacing bad files with fresh versions. To fix your current PC issue, here are the steps you need to take:
Download Fortect and install it on your PC.
Start the tool’s scanning process to look for corrupt files that are the source of your problem
Fortect has been downloaded by
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Are you getting the error message Currently, this hardware device is not connected to the computer (Code 45)? Don’t be alarmed, this post is meant just for you.
Several peripheral devices may be connected to the PC such as USB, mouse, keyboard, and other USB-connected devices. Error code 45 pops up especially on Windows 10 PC when the OS is unable to communicate with those devices.
The error implies that the connected hardware device is not being recognized by Windows, hence the error message.
However, this error can also be caused by corrupt Windows registry keys, outdated device drivers, or faulty hardware.
What to do when I get Hardware device is not connected to the computer (code 45) while using Bluetooth?If Bluetooth is not detecting devices on Windows, it’s possible that Bluetooth is not working because of hardware issues.
Using a USB adapter can also be a great workaround for this problem, so make sure that you consider that as well.
What can I do if Windows 10 won’t recognize hardware? 1. Perform a DISM scan2. Once the Command Prompt opens, input the following command: DISM /Online /Cleanup-Image /RestoreHealth
3. Press Enter to run the command.
4. The DISM scan will now start. This scan can take about 20 minutes or more, so don’t interfere with it or interrupt it.
5. When the scan completes, check if the issue persists.
If the previous method didn’t fix the problem for you, perhaps you might want to try running a DISM scan to fix the This Hardware Device is Not Connected to The Computer error. This is fairly simple to do, and you can do it by following the steps above.
Expert tip:
If the DISM scan fails, there are several things you can do to fix it. You can check your antivirus, clean your system image components, and more. If you experience this issue, take care of it first, and then move on to the other steps of the solution.
2. Update the driversThis is all good but manually updating all the drivers can be a tedious task. This job is a lot quicker and easier if you use a third-party solution that updates and fixes your drivers automatically.
These tools are especially easy to use and effective so you will get maximum results with little to no effort on your part.
3. Run Windows UpdateIn addition, you can fix the code 45 error problem by updating your Windows 10 OS to the latest version.
Microsoft constantly releases Windows updates so as to improve the system’s stability and fix various issues and errors associated with the startup error. Follow the steps above to update Windows 10 OS.
4. Repair PC RegistryThe simplest way to repair your Windows registry is to use a dedicated tool, such as Fortect. Alternatively, you can also use Microsoft’s System File Checker to check for system file corruption.
System File Checker verifies the integrity of all system files and repairs files with problems when possible.
5. Uninstall and reinstall the driverWindows users reported that they were able to solve the code 45 error problem using this fix so make sure you try it out.
6. Replace the USB DeviceIf you are still experiencing the code 45 error problem after trying all the fixes above, it is most likely that the device may be faulty.
Some hardware devices are not genuine, hence, they do not last long. You fix the faulty device if you have good technical knowledge or consider consulting a computer engineer to help you fix it.
However, we do recommend that you purchase a new USB device and install it on your Windows PC normally.
This will prevent the Currently this hardware device is not connected to the computer. (code 45) error on your PC.
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Fenwick Tree (Binary Indexed Tree)
The Fenwick Tree, also known as Binary Indexed Tree (BIT), is a data structure used to efficiently perform range queries and point updates on arrays. It is especially useful for problems that require frequent updates to array elements and range queries over the array, such as finding the sum of array elements in a given range.
The Fenwick Tree is an improvement over the naive approach of computing prefix sums or prefix products over the array, which takes O(n) time complexity for both updates and range queries. The Fenwick Tree can perform both operations in O(log n) time complexity, making it a popular choice for solving various competitive programming problems and algorithmic challenges.
Brief History and DevelopmentThe Fenwick Tree was first introduced by Peter Fenwick in 1994 as a solution to the problem of efficiently computing prefix sums for wavelet compression. It was later rediscovered by M. Binary Indexed Trees were also independently invented by K. J. Supowit in 1974 for the purpose of fast data compression.
Since then, the Fenwick Tree has been widely adopted in the competitive programming community and has found applications in various fields such as computer science, engineering, and finance.
Key Concepts and PrinciplesThe Fenwick Tree is based on the principle of cumulative frequency, where each node in the tree stores the sum of a certain range of elements in the array. The nodes are organized in a binary tree structure, where each node represents a range of array elements.
To compute the sum of a range [1, i] in the original array, we start by traversing the binary tree from i to the root, adding the value of each node encountered to the final result. To update an element in the array, we simply update the corresponding node in the tree and all its ancestors.
The key concept behind the Fenwick Tree is the use of binary representation to efficiently compute the range sum and perform updates. Specifically, each node in the tree is responsible for storing the sum of a range of elements, where the range is determined by the binary representation of its index.
For example, the sum of elements [1, 4] in the array is stored in node 4, since 4 in binary is 100, and the range of elements [1, 4] covers the first 4 elements in the array.
Pseudocode and Implementation DetailsThe Fenwick Tree can be implemented using an array of size n+1, where n is the length of the original array. The extra element is used to simplify node indexing, since node i in the tree corresponds to index i in the array.
def update(bit, i, val): # Add val to the i-th element in array n = len(bit) while i <= n: bit[i] += val i += i & -i def query(bit, i): # Compute the sum of elements [1, i] in array res = 0 res += bit[i] i -= i & -i return resThe update function takes a Binary Indexed Tree bit, an index i, and a value val, and updates the Fenwick Tree by adding val to the i-th element in the array. The while loop iteratively updates the tree by adding val to the current node, then moves to its parent node by adding the least significant bit of i.
The query function takes a Binary Indexed Tree bit and an index i, and computes the sum of elements [1, i] in the original array. The while loop iteratively traverses the tree from i to the root, adding the value of each node encountered to the final result, then moves to the next node by removing the least significant bit of i.
Examples and Use Cases Example 1: Computing Prefix SumSuppose we have an array of integers a = [1, 2, 3, 4, 5, 6, 7, 8], and we want to compute the prefix sums of the array. The prefix sum of an array is defined as the sum of elements [1, i] for each index i in the array.
We can use the Fenwick Tree to compute the prefix sums in O(n log n) time complexity, where n is the length of the original array.
def build_bit(a): # Build the Binary Indexed Tree from array a n = len(a) bit = [0] * (n+1) for i in range(1, n+1): update(bit, i, a[i-1]) return bit a = [1, 2, 3, 4, 5, 6, 7, 8] bit = build_bit(a) # Computing prefix sum of array a for i in range(1, len(a)+1): print(query(bit, i))The output of the above code is:
1 3 6 10 15 21 28 36 Example 2: Finding the Sum of Elements in a Given RangeSuppose we have an array of integers a = [1, 2, 3, 4, 5, 6, 7, 8], and we want to find the sum of elements in the range [3, 6] of the array.
We can use the Fenwick Tree to answer this query in O(log n) time complexity, where n is the length of the original array.
a = [1, 2, 3, 4, 5, 6, 7, 8] bit = build_bit(a) # Finding sum of elements [3, 6] in array a print(query(bit, 6) - query(bit, 2))The output of the above code is:
18 Advantages
The Fenwick Tree has a small memory footprint and can be implemented using a one-dimensional array, making it efficient in terms of both space and time complexity.
The Fenwick Tree supports both range queries and point updates in O(log n) time complexity, making it useful for solving various algorithmic challenges and problems that require frequent updates to array elements and range queries over the array.
The Fenwick Tree can only be used for operations that are associative and have an inverse, such as addition and multiplication. It cannot be used for non-associative operations such as finding the maximum or minimum element in a range.
The Fenwick Tree has limited applicability in certain fields such as natural language processing and image processing, where the operations on the data are not associative.
Related Algorithms or VariationsThe Fenwick Tree is related to other data structures such as Segment Tree and Binary Search Tree.
The Segment Tree is a similar data structure that also supports range queries and point updates over an array. The main difference between the Segment Tree and the Fenwick Tree is that the Segment Tree is a tree-based data structure, whereas the Fenwick Tree is based on the binary representation of indices.
The Binary Search Tree is another data structure that supports range queries and point updates over an array. However, the Binary Search Tree has a worst-case time complexity of O(n) for both operations, whereas the Fenwick Tree has a worst-case time complexity of O(log n).
ConclusionThe Fenwick Tree, also known as Binary Indexed Tree, is a data structure used to efficiently perform range queries and point updates on arrays. It is based on the principle of cumulative frequency and uses the binary representation of indices to efficiently compute the range sum and perform updates. The Fenwick Tree has a small memory footprint and can be implemented using a one-dimensional array, making it efficient in terms of both space and time complexity. It supports both range queries and point updates in O(log n) time complexity, making it useful for solving various algorithmic challenges and problems. However, it can only be used for operations that are associative and have an inverse, and has limited applicability in certain fields such as natural language processing and image processing.
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